DOC.
C 55.13:
NWS38
<*»* , ° ,r «v
^irts o« *
NOAA Technical Report NWS 38
Hurricane Climatology
for the Atlantic and
Gulf Coasts of the
United States
Silver Spring, MD
April 1987
The
%?
***.
*h Q
Study completed under agreement EMW-84-E-1589 for
FEDERAL EMERGENCY MANAGEMENT AGENCY
U.S. DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
National Weather Service
NOAA TECHNICAL REPORTS
National Weather Service Series
The National Weather Service (NWS) observes and measures atmospheric phenomena; develops and distrib-
utes forecasts of weather conditions and warnings of adverse weather; collects and disseminates weather
information to meet the needs of the public and specialized users. The NWS develops the national
meteorological service system and improves procedures, techniques, and dissemination for weather and
hydrologic measurements, and forecasts.
NWS series of NOAA Technical Reports is a continuation of the former series, ESSA Technical Report
Weather Bureau (WB).
Reports listed below are available from the National Technical Information Service, U.S. Depart-
ment of Commerce, Sills Bldg. , 5285 Port Royal Road, Springfield, VA 22161. Prices vary. Order by
accession number (given in parentheses).
ESSA Technical Reports
WB 1 Monthly Mean 100-, 50-, 30-, and 10-Millibar Charts January 1964 through December 1965 of the
IQSY Period. Staff, Upper Air Branch, National Meteorological Center, February 1967, 7 p,
96 charts. (AD 651 101)
WB 2 Weekly Synoptic Analyses, 5-, 2-, and 0.4-Mb Surfaces for 1964 (based on observations of the
Meteorological Rocket Network during the IQSY). Staff, Upper Air Branch, National Meteorologi-
cal Center, April 1967, 16 p, 160 charts. (AD 652 696)
WB 3 Weekly Synoptic Analyses, 5-, 2-, and 0.4-Mb Surfaces for 1965 (based on observations of the
Meteorological Rocket Network during the IQSY). Staff, Upper Air Branch, National Meteorologi-
cal Center, August 1967, 173 p. (AD 662 053)
WB '+ The March-May 1965 Floods in the Upper Mississippi, Missouri, and Red River of the North Basins.
J. L. H. Paulhus and E. R. Nelson, Office of Hydrology, August 1967, 100 p.
WB 5 Climato logical Probabilities of Precipitation for the Conterminous United States. Donald L.
Jorgensen, Techniques Development Laboratory, December 1967, 60 p.
WB 6 Climatology of Atlantic Tropical Storms and Hurricanes. M. A. Alaka , Techniques Development
Laboratory, May 1968, 18 p.
WB 7 Frequency and Areal Distributions of Tropical Storm Rainfall in the United States Coastal Region
on the Gulf of Mexico. Hugo V. Goodyear, Office of Hydrology, July 1968, 33 p.
WB 8 Critical Fire Weather Patterns in the Conterminous United States. Mark J. Schroeder, Weather
Bureau, January 1969, 31 p.
WB 9 Weekly Synoptic Analyses, 5-, 2-, and 0.4-Mb Surfaces for 1966 (based on meteorological rocket-
sonde and high-level rawinsonde observations). Staff, Upper Air Branch, National Meteorological
Center, January 1969, 169 p.
WB 10 Hemispheric Tele connect ions of Mean Circulation Anomalies at 700 Millibars. James F. O'Connor,
National Meteorological Center, February 1969, 103 p.
WB 11 Monthly Mean 100- , 50-, 30-, and 10-Millibar Charts and Standard Deviation Maps, 1966-1967.
Staff, Upper Air Branch, National Meteorological Center, April 1969, 124 p.
WB 12 Weekly Synoptic Analyses, 5-, 2-, and 0.4-Millibar Surfaces for 1967. Staff, Upper Air Branch,
National Meteorological Center, January 1970, 169 p.
NOAA Technical Reports
NWS 13 The March-April 1969 Snowmelt Floods in the Red River of the North, Upper Mississippi, and Mis-
souri Basins. Joseph L. H. Paulhus, Office of Hydrology, October 1970, 92 p. (COM-71-50269)
NWS 14 Weekly Synoptic Analyses, 5-, 2-, and 0.4-Millibar Surfaces for 1968. Staff, Upper Air Branch,
National Meteorological Center, May 1971, 169 p. (COM-71-50383)
NWS 15 Some Climato logical Characteristics of Hurricanes and Tropical Storms, Gulf and East Coasts of
the United States. Francis P. Ho, Richard W. Schwerdt, and Hugo V. Goodyear, May 1975, 87 p.
(C0M-7 5-1 1088)
(Continued on inside back cover)
'.Vhix'oliY OF
•- «i013 LIBKAKY
■'■■■JA-CHAMPAIGN
STACKS
NOAA Technical Report NWS 38
Hurricane Climatology
for the Atlantic and
Gulf Coasts of the
United States
Francis P. Ho, James C. Su, Karen L. Hanevich,
Rebecca J. Smith and Frank P. Richards
Silver Spring, MD
April 1987
Government Document
Book Stacks
Study completed under agreement EMW-84-E-1589 for
FEDERAL EMERGENCY MANAGEMENT AGENCY
U.S. DEPARTMENT OF COMMERCE
Malcolm Baldrige, Secretary
National Oceanic and Atmospheric Administration
Anthony J. Calio. Under Secretary
National Weather Service
Richard E. Hallgren, Acting Assistant Administrator
Digitized by the Internet Archive
in 2012 with funding from
University of Illinois Urbana-Champaign
http://archive.org/details/hurricaneclimatoOOhofr
TABLE OF CONTENTS
Page
Abs tract 1
1 . Introduction I
1 .1 Authorization. 1
1.2 Purpose 2
1.3 Scope of report 2
1.4 Relation to flood insurance studies 4
1.5 Previous studies. 5
2. Data 5
2.1 Introduction 5
2.2 Sources of data 6
2.3 Hurricane central pressure (P Q ) data 23
2.3.1 Central pressure criteria based on balanced wind model 2 4
2.3.2 Central pressure adjustments 2 4
2.3.3 Revised central pressure from previous studies 2 5
2.4 Hurricane radius of maximum winds (R) data 2 5
2.4.1 Source of radius of maximum winds 2 6
2.4.1.1 Radius of maximum winds from aerial reconnaissance 26
2.4.1.2 Radius of maximum winds from wind records 2 7
2.4.1.3 Radius of maximum winds from eye radius. 28
2.4.1.4 Radius of maximum winds from pressure fit...... 2 8
2.4.1.5 Radius of maximum winds from Monthly Weather Review 28
2.5 Speed and (T) direction (9) of forward motion 2 8
2.5.1 Source of T and 9 data 28
2.5.2 T and 9 data used in probability distributions 30
3. Meteorological parameters and their interrelations......... 30
3.1 Introduction. 30
3.1.1 Overview of the statistical study... 30
3.1.2 Scope of the chapter 3 1
3.2 Considerations of data samples for statistical tests 31
3.2.1 Forward speed 32
3.2.2 Forward direction 34
3.3 Homogeneity of the hurricane data samples.. 3 4
3.3.1 Methods for testing the homogeneity of storm parameters 3 5
3.3.2 Comparison of results from different homogeneity tests 3 7
3.3.2.1 Meteorological method 37
3.3.2.2 Cluster analysis 38
3.3.2.3 Discriminant analysis 38
3.3.2.4 Principal component analysis 39
3.3.3 Selection of hurricane groups for independence testing 40
3.3.3.1 Gulf coast 42
3.3.3.2 Florida coast 42
3.3.3.3 Atlantic coast 43
Page
3.4 Interrelations between hurricane parameters 43
3.4.1 Brief review of previous studies 43
3.4.2 Methods for testing the interrelations between hurricane
parameters 44
3.4.2.1 Contingency table with Chi-square test 44
3.4.2.2 Spearman test 44
3.4.3 Comparison of results from different independence tests 45
3 .5 Discussion 45
4. The joint probability question: Central pressure versus
radius of maximum winds 50
4 .1 Introduction 50
4.2 Central pressure versus radius of maximum winds 50
4.3 Meteorological analysis 52
4.4 Discussion of analysis 55
4 .5 Conclusions 59
5. Other joint probability questions 59
5 . 1 Introduction 59
5.2 Forward speed versus direction of storm motion 60
5.3 Central pressure versus direction of storm motion 61
5.3.1 Gulf coast 61
5.3.2 Atlantic coast.. 64
5.3.2.1 Atlantic coast, south of 33 ,5°N 64
5.3.2.2 North Atlantic coast 66
5.4 Cape Hatteras area 66
5.4.1 Parameters for landfalling hurricanes from northeast
quadrant.. 66
5.4.2 Parameters for landfalling hurricanes from southeast
quadrant 67
5.4.3 Landfalling track frequency 67
6. Frequency of hurricane and tropical storm occurrences 67
6.1 Classification of hurricanes and data 67
6.2 Frequency of landfalling tropical cyclones..... 72
6.2.1 Direct-count method........ 72
6.2.1.1 Objective smoothing procedure 75
6.2.1.2 Evaluation of procedure 7 5
6.2.2 Discussion of results 7:
6.2.2.1 Areas of high entry frequencies 7
6.2.2.1 (a) Northwest Florida 77
6.2.2.1 (b) South Florida 77
6.2.2.1 (c) Upper Texas coast 78
6.2.2.1 (d) Cape Hatteras 78
6.2.2.2 Areas of low entry frequencies 78
6.2.2.2 (a) East coast 78
6.2.2.2 (b) Gulf coast 78
6.3 Frequency of exiting tropical cyclones 78
6. 3.1 Analysis * 78
6.3.2 Results and discussion
6.3.2.1 Gulf coast 79
iv
Page
6.3.2.2 Atlantic coast 79
6.3.2.3 Application in tide-frequency analysis 79
6.4 Frequency of alongshore tropical cyclones 81
6.4.1 Analysis 81
6.4.2 Results and discussion 85
7. Central pressure 85
7 .1 Introduction 85
7 .2 Analysis 86
7.3 Results 89
7.3.1 Pressure minima 89
7.3.1.1 South Florida minimum..... 89
7.3.1.2 South Texas minimum 92
7.3.1.3 Carolinas and southern New England minima 92
7.3.1.4 Mississippi Delta minimum 92
7.3.2 Pressure maxima 92
7.3.2.1 Cross City, Florida, maximum 92
7.3.2.2 Delaware Bay maximum 93
7.3.2.3 Jacksonville maximum.... 93
7.3.2.4 Northern New England coastal maximum 93
8. Radius of maximum winds 94
8.1 Analysis 94
8.1.1 Gulf of Mexico 95
8.1.2 Atlantic coast 95
8.2 Evaluation of the analysis 95
8.2.1 Gulf coast 95
8.2.1.1 Florida and Mexico minima 95
8.2.1.2 Mississippi-Florida panhandle maximum..... 95
8.2.2 Atlantic coast 95
8.3 Radius of maximum winds for intense hurricanes 98
9. Speed and direction of storm motion 98
9.1 Speed of storm motion 98
9.1.1 Forward speed of landf ailing tropical cyclones 98
9.1.1.1 Analysis 98
9.1.1.2 Results and discussion 98
9.1.2 Forward speed of bypassing tropical cyclones 102
9.2 Direction of storm motion 102
9.2.1 Direction of storm motion for landfalling tropical
eye lones 102
9.2 .1.1 Analysis 102
9.2.1.2 Results and discussion 103
9.2.1.2 (a) Gulf coast 106
9.2.1.2 (b) East coast, south of Cape Hatteras 107
9.2.1.2 (c) East coast, north of Cape Hatteras 107
9.2.1.3 Areas of discontinuous direction profile 107
9.2.2 Direction of storm motion for bypassing tropical cyclones... 107
10. Adjustment of hurricane intensity for filling overland 108
10.1 Introduction 108
10.2 Index for overland filling 108
Page
10.3 Previous observational studies .. 109
10.4 Analysis of data 109
10.5 Filling rates by region 110
10.6 Results 121
11. Application of hurricane parameters 123
11.1 Introduction 123
11.2 Landfall point 123
11.3 Peripheral pressure 124
11.4 Probability distributions of hurricane parameters and
frequency of occurrence 12 4
11.5 Applications of profiles of probability distributions for
hurricane parameters. 12 7
11.6 Exiting tropical cyclones 13 6
12. Summary and discussion... 136
12.1 Frequency of tropical cyclone occurrences 13 7
12.2 Probability distribution of storm parameters 138
12.3 Independence of parameters.... 138
Acknowledgments 139
References 140
Appendix A Detailed analysis of selected storms 147
A.l Introduction 147
A.2 Hurricane Alicia, August 15-21, 1983 147
A .2 .1 Introduction. 147
A.2 .2 Previous reports 147
A.2 .3 Sources of data 148
A.2 .4 General meteorological situation 149
A.2 .5 Detailed meteorological analysis... 149
A.2. 5.1 Storm track 149
A.2 .5.2 Forward speed... 150
A.2 .5.3 Central pressure 152
A.2. 5. 4 Wind analysis 154
A.2. 5. 5 Radius of maximum winds 156
A.2 .6 Discussion 159
A.3 Hurricane David, September 2-5, 1979 160
A. 3 .1 Introduction 160
A.3 .2 Previous studies * 162
A.3 .3 Aircraft data..... 163
A.3. 4 Central pressure 164
A.3 .4.1 P from aerial reconnaissance. 164
A.3 .4.2 P from land station observations 164
A. 3. 4.3 Pressure fit at the coast 164
A.3. 4. 4 Time variation of P 164
A.3 .5 Radius of maximum winds 170
A.3. 5.1 R from aerial reconnaissance...... 170
A. 3. 5.2 R from land station observations 170
A.3 .5.3 Time variation of radius of R 174
A. 4 Hurricane Allen, August 2-10, 1980 174
A. 4.1 Introduction . 174
A. 4.2 Previous reports 176
A. 4. 3 Reconnaissance flight data.. 177
Page
A. 4. 4 Central pressure analvsis 177
A. 4. 5 Wind analvsis 177
A. 4. 6 Time variation of central pressure and radius of maximum
winds ' 1 82
A. 4. 7 Relation of P Q and R in Hurricane Allen 182
Appendix B Statistical methods for tests of homogeneitv and
independence 185
B .1 Introduction 18 5
B .2 Methods for the test of homogeneity 185
B.2.1 Cluster analysis 185
B.2.1.1 Description of the method 185
B.2.1. 2 Rationale for choice 186
B.2.1. 3 Limitations of the method 187
B.2.1. 4 Interpretation of the results 187
B.2.2 Discriminant analysis 187
B.2.2.1 Description of the method 187
B.2.2 .2 Rationale for choice 187
B.2.2 .3 Limitations of the method 187
B.2.2. 4 Interpretation of the results 188
B.2.3 Principal component analysis 188
3.2.3.1 Description of the method 188
B.2.3 .2 Rationale for choice 188
B.2.3 .3 Limitations of the method 188
B.2.3 .4 Interpretation of the results 188
B.2.4 Mann-Whitney test 189
B.2.4.1 Description of the method 189
B.2.4.2 Rationale for choice 190
B.2.4.3 Limitations of the method 190
B.2.4.4 Interpretation of the results 190
B.3 Methods for the test of independence 190
B.3.1 Spearman test 191
B.3. 1.1 Description of the method..... 191
B.3. 1.2 Rationale for choice. 191
B.3. 1.3 Limitations of the method 191
B.3. 1.4 Interpretation of the results 191
B.3. 2 Contingency table with Chi-square test 192
B.3 .2.1 Description of the method 192
B.3 .2 .2 Rationale for choice 192
B.3. 2.3 Limitations of the method 192
B.3 .2 .4 Interpretation of the results 192
Appendix C Plotting position formula 192
C .1 Introduction 192
C.2 Criteria for evaluation 192
C.3 Evaluation of plotting position formulae 194
C.4 Comparison of formulae 194
LIST OF FIGURES
Number Page
1 Locator map with coastal distance intervals marked (nmi) 3
2 Hourly observations of wind speed and direction, and distance of
Allen's center from Brownsville, Texas 27
3 Radius of maximum winds versus inner radar eye radius 2 9
4 Difference between the radius of maximum winds and the inner radar
eye radius versus maximum wind speed 2 9
5 Forward speed of landfalling hurricanes and tropical storms versus
milepost (a) along the Gulf coast of Florida, and (b) along the
Atlantic coast 33
6 Possible homogeneous regions for landfalling hurricane
parameters * 36
7 Plot of the second principal component versus the first principal
component 40
8 Central pressure of landfalling hurricanes versus milepost 41
9 Interrelations between parameters of landfalling hurricanes for
the Gulf and Atlantic coasts of the United States 46
10 Landfalling hurricane parameters versus milepost for the Atlantic
coast. 48
11 Location and minimum central pressure of extreme hurricanes 54
12 Tracks of extreme hurricanes 56
13 Same as Figure 12 57
14 Plot of P versus R for extreme hurricanes listed in Table 16 58
15 Scatter diagram of direction versus speed of forward motion for
hurricanes landfalling on the Atlantic coast 60
16 Probability distribution of forward speed of (a) landfalling, and
(b) alongshore hurricanes in the vicinity of Charleston, South
Carolina, for the period 1886-1973 62
17 Plot of forward direction versus milepost for the landfalling
hurricanes on the Gulf coast of the United States 63
18 Variation with latitude of direction of forward motion for
hurricanes landfalling on the Atlantic coast... 63
vi i i
Number Page
19 Histogram for direction of storm motion for the 2.5° latitude and
longitude block centered about Key West, Florida 65
20 Track, of tropical storms and hurricanes showing motion from
northeast 68
2 1 Cumulative probability curve of central pressure for landf ailing
tropical cyclones near Wright Monument, North Carolina 69
22 Cumulative probability curve of speed of storm motion adapted for
landfalling tropical cyclones near Wright Monument, North
Carolina. 69
23 Frequency of landfalling hurricanes and tropical storms 70
24 Smoothed coastline obtained by applying the objective smoothing
function 71
2 5 Map showing extensions of west coast of Florida and the Atlantic
coast through the Florida Keys..... 73
2 6 Count of landfalling tropical storms and hurricanes (1871-1984)
by 50-nmi segments of a smoothed coastline 74
27 Frequency of landfalling tropical cyclones (1871-1984) for the
Gulf and Atlantic coasts of the United States.. 76
28 Frequency of exiting hurricanes and tropical storms (1871-1974).... 80
2 9 Tide frequencies at Wright Monument, North Carolina, for several
classes of storms 81
3 Accumulative count of hurricane and tropical storm tracks passing
the coast at sea (1871-1984) 82
3 1 Cumulative frequency of tropical cyclones bypassing the Gulf coast
at selected distances offshore (1871-1984) 83
32 Cumulative frequency of tropical cyclones bypassing the Atlantic
coast at selected distances offshore (1871-1984) 84
33 Cumulative probability curve of central pressure of hurricanes
landfalling within (a) 250 nmi of milepost 250, near Corpus
Christi, Texas, and (b) 200 nmi of milepost 1600 near Vero
Beach Florida a 88
3 4 Probability distribution of central pressure for hurricanes
landfalling on the Gulf coast (1900-84) 90
35 Same as Figure 34, but for Atlantic coast hurricanes... 91
Number Page
36 Cumulative probability curve of radius of maximum winds for
hurricanes landf ailing within (a) 2 50 nmi of milepost 2 50, near
Corpus Christi, Texas, and (b) 200 nmi of milepost 1600, near
Vero Beach, Florida 94
37 Probability distribution of radius of maximum winds for hurricanes
landf ailing on the Gulf coast (1900-84) 96
38 Same as Figure 37, but for Atlantic coast hurricanes 97
3 9 Cumulative probability curve of forward speed of tropical cyclones
landfalling within (a) 250 nmi of milepost 250, near Corpus
Christi, Texas, and (b) 200 nmi of milepost 1600, near Vero
Beach, Florida 99
40 Probability distribution of forward speed for tropical cyclones
landfalling on the Gulf coast (1900-84) 100
41 Same as Figure 40, but for Atlantic coast tropical cyclones........ 101
42 Cumulative probability curve of direction of storm motion of
tropical cyclones landfalling within (a) 100 nmi of milepost 2 50,
near Corpus Christi, Texas, and (b) 100 nmi of milepost 1600,
near Vero Beach, Florida 103
43 Probability distribution for direction of storm motion for
tropical cyclones landfalling on the Gulf coast (1900-84) 104
44 Same as Figure 43, but for the Atlantic coast south of Cape
Hatteras 105
45 Same as Figure 43 , but for the Atlantic coast north of Cape
Hatteras 106
46 Pressure profiles after landfall for (a) hurricane Frederick
September 1979 and (b) Hurricane Alicia, August 1983 HI
47 Map showing geographical regions used to study filling rates 112
48a Variation with time after landfall of filling rate of hurricanes
listed in region A of Table 19 114
48b Same as Figure 48a 115
49 Filling rates for hurricanes of various intensities for region A
(Gulf coast, west of Apalachicola, Florida) 116
50 Comparison of filling rates for various hurricanes crossing the
Florida peninsula and Che filling curve for region B from
Schwerdt et al. (1979) 118
Number Page
51 Filling rates for hurricanes of various intensities for region B
(southern Florida) 119
52 Variation with time after landfall of filling rates for Hurricanes
Hazel (1954), Gracie (1959), and David (1979) 120
53 Variation with time of filling rates for New England hurricanes.... 12 1
54 Filling rate for hurricanes in region C (Atlantic coast, north of
Georgia ) 12 2
55 Plot of cumulative counts of alongshore storms versus distance
from coast for Vero Beach, Florida (milepost 1600) 12 6
56 Cumulative probability curves of P Q for designated locations....... 133
57 Cumulative probability curve for pressure deficit at Vero Beach,
Florida 13 5
A.l Hurricane track for Alicia, 0000 CST August 16 through 1200 CST
August 18, 1983 150
A.2 Hurricane eye position obtained from radar, aircraft
reconnaissance penetration fixes, and satellite observations 151
A. 3 Minimum pressure recorded at land stations and by aircraft
reconnaissance during Hurricane Alicia 152
A. 4 Variation of minimum central pressure estimates for Hurricane
Alicia 153
A. 5 Hourly observations of sea-level pressure and surface wind speed
recorded at Houston Intercontinental Airport, Texas 155
A. 6 Same as Figure A. 5, but for Baytown, Texas 156
A. 7 Composite isotach analysis for Hurricane Alicia, centered at
2240 GMT, August 17, 1983 157
A. 8 Streamline and 10-m isotach analysis for Hurricane Alicia,
0730 GMT, August 18, 1983.. 158
A. 9 Flight-level winds recorded along radials through the center of
Hurricane Alicia, 1352-1433 GMT, August 17, 1983 159
A. 10 Radius of primary and secondary wind maxima in Hurricane Alicia,
August 17-18, 1983 160
A.ll Track with central pressures for Hurricane David,
September 2-5, 1979. 161
xi
Number Page
A. 12 Reconnaissance flight pattern, designated as star pattern used in
Hurricanes David and Allen 163
A. 13 Sea-level pressure observed during passage of Hurricane David,
(September 1979) at (a) Shuttle Airport, Florida,
and (b) Savannah (Municipal Airport), Georgia 165
A. 14 Pressure-profile curve during Hurricane David (a) for Florida coast
at 2100 GMT, September 3, 1979, (b) Georgia coast at 1800 GMT,
September 4, 1979 166
A. 15 Central pressure (sea-level) for Hurricane David,
September 3-5, 1979 167
A. 16 Flight-level winds recorded along radials through the center of
Hurricane David, (a) 2308-2356 GMT, September 2, (b) 0644-
0748 GMT, September 4, and (c) 1751-1841 GMT, September 4, 1979.. 169
A. 17a Wind speed and direction at Shuttle Airport, Florida, during
the passage of Hurricane David, September 2-4, 1979.. 171
A. 17b Wind speed and direction at Savannah, Georgia, during the passage
of Hurricane David, September 3-5 , 1979 172
A. 18 Radial distances (from eye center) of wind maxima in Hurricane
David, September 2-5, 1979 173
A. 19 Track of Hurricane Allen, August 2-11, 1980 175
A.20 Reconnaissance flight patterns used in Hurricane Allen... 179
A.2 1 Central pressure for Hurricane Allen, (a) August 3-7, and (b)
August 7-10, 1980 180
A.22 Flight-level winds recorded along radials through the center
of Hurricane Allen, 1535-1627 GMT, August 5, 1980 181
A.23 Flight-level winds recorded along radials through the center of
Hurricane Allen, 1844-1945 GMT, August 7, 1980 181
A. 2 4 Composite map of flight-level winds recorded between 02 00 and
0400 GMT, August 9, 1980 ' 182
A.2 5 Central pressure and radial distances (from eye center)
of wind maxima in Hurricane Allen, August 3-10, 1980 183
A.2 6 Concurrent observations of central pressure and radius of maximum
winds for Hurricane Allen, August 3-9, 1980 184
B.l Levels two through nine of the hierarchical clustering of
la ndf ailing hurricanes. 186
C.l Comparison of plotting position formulae for N = 10 195
LIST OF TABLES
Number Page
1 Hurricanes with central pressure < 982 mb, ranked in
chronological order from 1900-84. Gulf coast United States 7
2 Hurricanes with central pressure < 982 mb ranked in chronological
order from 1900-84. East coast United States 14
3 Miscellaneous Florida hurricanes with central pressure < 982 mb
ranked in chronological order from 1900-1984 20
4 Hurricanes with revised central pressure 2 6
5 Forward speed of hurricanes and tropical storms for selected
portions of the coast 32
6 Initially selected coastal segments.. 35
Results of Mann-Whitney test for a priori selection of coastal
segments in the Gulf of Mexico.. 3 7
8 Results of Mann-Whitney test for modified segments of the Gulf
coast 38
9 Percentages of variance accounted for by principal components...... 39
10 Loading of hurricane parameters in the principal components which
account for more than 12 percent of variance.... 39
11 Coastal segments that include homogeneous hurricane parameters for
the test of independence 41
12 Breakpoint values for contingency tables 44
13 Sample sizes of paired parameters of landfalling hurricanes for
coastal segments 45
14 An example of a general two-by-two contingency table 51
15 Frequency of occurrence of different storm radii in two different
class intervals of hurricane intensity observed in the Gulf of
Mexico , 1900-84 52
16 Severe hurricanes since 1900 with P Q < 93 mb 53
17 Comparison of speeds of landfalling and alongshore storms for the
vicinity of Charleston, South Carolina 61
18 Partition of P q and for landfalling hurricanes striking the
Atlantic coast south of 33.5°N , 64
x i i i
Number Page
19 Selected landfalling hurricanes (1928-1983) used to estimate
overland filling rates 113
2 Changes in hurricane pressure deficits due to overland filling 117
2 1 Summary sheet of information needed from this report for
surge-frequency computations 12 8
22a Summary sheet for Vero Beach, Florida 130
22b Summary sheet' for 50 nmi north of Vero Beach, Florida 13 1
22c Summary sheet for 50 miles south of Vero Beach, Florida 132
23 Tropical cyclone parameters Vero Beach, Florida 13 4
2 4 Data used in this report for probability analyses 137
A.l Time, flight pattern, and flight level of NOAA/RFC missions into
Hurricane David, September 1979 162
A.2 Time, flight pattern, and flight level of NOAA/RFC missions into
Hurricane Allen, August 1980 178
C.l List of plotting position formulae 193
C .2 List of plotting position formulae in the descending order of
their p *s 194
r m
HURRICANE CLIMATOLOGY FOR THE ATLANTIC AND GULF COASTS
OF THE UNITED STATES
Francis P. Ho, James C. Su, Karen L. Hanevich,
Rebecca J. Smith and Frank Richards
Water Management Information Division
Office of Hydrology
National Weather Service
National Oceanic and Atmospheric Administration
ABSTRACT A climatology of hurricane factors important
to storm-surge modeling is presented for the Atlantic
and Gulf coasts of the United States. A smoothed
frequency of hurricanes and tropical storms entering,
exiting, and passing within 150 nmi of the coast
during the period 1871-1984 is given. The central
pressure and radius of maximum winds for hurricanes
occurring during the 85-year period, 1900-84, were
obtained from analysis of available hurricane data.
Direction and speed of storm motion for hurricanes and
tropical storms at the time they crossed the coast
were also analyzed for the same 85-year period. The
cumulative probability curves of each factor were
plotted and analyzed for each 50-nmi interval along
the coast. Selected probability levels of each
distribution were summarized, and smoothed variations
along the coast were obtained. Statistical
independence of hurricane parameters has also been
examined and interrelations of central pressure and
radius of maximum winds investigated.
1 . INTRODUCTION
1.1 Authorization
The National Flood Insurance Act of 1968, Title XIII, Public Law 90-448,
enacted August 1, 1968, authorized and provides for a National Flood Insurance
Program to insure residences and small businesses against hazard of damage or
destruction by flood. The Federal Insurance Administration (FIA), a part of the
Federal Emergency Management Agency (FEMA), is the executive agency for the
National Flood Insurance Program. In July 1982 , a Joint Technical Assistance
Work Plan was signed between FEMA and the National Oceanic and Atmospheric
Administration (NOAA). The plan, among other things, allows for the National
Weather Service (NWS), NOAA, to provide technical support Co FEMA upon request.
Authorization for this particular study is Project No. 53967 under agreement
No. EMW-84-E-1589 between the FIA, FEMA and the NWS, NOAA, dated March 15, 1984
and duly signed April 2 5, 1984.
1 .2 Purpose
The Federal Insurance Administration, FEMA, requested the NWS, NOAA, to develop
a comprehensive and authoritative set of hurricane clima tological statistics for
the Atlantic and Gulf Coasts of the United States. These statistics are
prerequisites in tidal flood-frequency analyses which are essential to establish
flood insurance criteria for a given community. Coastal tidal inundations on the
Gulf and Atlantic coasts of the United States are primarily caused by
hurricanes. Therefore, the characteristics of these storms are the beginning
point in making tidal flood-frequency analyses. The present study is a
climatological assessment of the central pressure, radius of maximum winds, and
other characteristics of hurricanes along the U.S. Atlantic and Gulf coasts in a
manner suitable for determining the frequency of storm surge levels. It includes
only the atmospheric characteristics of hurricanes and does not include surge
levels that are the subject of other reports.
The present study is an update and revision of an earlier study published as
NOAA Technical Report NWS-15 (Ho et al 197 5), which will hereafter be referred to
as TR 15. TR 1 5 presented a climatology of hurricane parameters important to
storm-surge modeling along the U.S. Gulf and Atlantic Coasts. This climatology
was an analysis of available hurricane data, with storm tracks from 1871 through
1973, and also included data for other meteorological variables since 1900.
TR 15 included the cumulative probability distributions of each hurricane factor
analyzed at 50-nmi intervals along the coast, and smoothed variations of each
factor at selected probability levels along the coast were presented. A smoothed
frequency of tropical storms and hurricanes entering and exiting the coast as
well as those storms passing within 150 nmi of the coast was also given in
TR 15. The question of joint probability among the various factors was discussed
qualitatively, but formal statistical tests were not considered in TR 15.
The National Research Council of the National Academy of Sciences (NAS)
reported on an evaluation of the FEMA Model for estimating potential coastal
flooding from hurricanes (National Academy of Sciences 1983). This NAS report
concluded that the basic approach used by FEMA is sound and appropriate for
estimating 100-yr flood elevations in communities where severe flooding is caused
by hurricane storm surges. However, the Advisory Committee of the NAS made
several recommendations regarding the way in which coastal flood studies are
conducted. The committee recommended, among other things, that the selection of
storm samples and the adoption of appropriate interdependency assumptions should
be carried out in a centralized way by an organization with the necessary
expertise in hurricane climatology. The committee concluded that inter-
dependencies among storm parameters, particularly among storm intensity, size,
and direction, should be determined by that organization on a regional basis and
an appropriate method for handling these interdependencies when applying the
probability procedure to coastal flood elevations should be developed.
1.3 Scope of Report
The geographical region covered by the report is the U.S. Gulf and Atlantic
coasts from Texas to Maine (fig. 1). The first objective was to define, clima-
tologically, the frequency of hurricanes and tropical storms influencing each
coastal segment. This was done for three classes of storms — those entering the
coast from the sea (entering or landf ailing) , those having entered the coast and
then proceeding from land to sea (exiting), and those moving parallel to the
v^ino'dS"* 1
, ,»vi* 3000
* -2900
SfcT'N
Iaiyestoh .
500 / \
400 ^ U 600 700
-#
300
-200
J00_
1200 -— • -r,So
G U| L
O f
Figure 1« — Locator map with coastal distance intervals marked (max).
3
coast, with the center remaining at sea, but within 150 nmi of the point under
consideration (alongshore or bypassing). These frequencies are presented in
Chapter 6.
The second objective was to develop cumulative probability distributions for
four hurricane parameters: (1) central pressure (P Q ), an index of storm inten-
sity, (2) the radius of maximum winds (R), an index of storm size, (3) forward
speed of the storm (T), and (4) direction of storm motion (9). Each of these
factors influences the capability of the storm to produce storm tides. Chapter 2
discusses in detail the data sources and analyses from which the hurricane
characteristics were obtained. Probability distributions and their along-coast
variations for each parameter are presented in Chapters 7 through 9 of this
report.
The statistical independence of hurricane parameters is considered in
Chapter 3. The homogeneity of each parameter along the Gulf and Atlantic coasts
was tested separately. Interrelations between pairs of parameters have been
examined in Chapter 3. Non-linear relations between central pressure (P ) and
radius of maximum winds (R) are discussed both dynamically and statistically in
Chapter 4. For this purpose, the data base for P q and R was extended to include
extreme hurricanes in the Caribbean and the Gulf of Mexico. Chapter 5 considers
other conditional probability questions that are important to the currently used
joint probability approach for tide-frequency analysis.
Chapter 10 examines changes in the wind and pressure fields due to the filling
of hurricanes overland. Finally, Chapter 11 discusses application of the results
of this study to flood insurance studies.
1.4 Relation to Flood Insurance Studies
Meteorological parameters P R, 9 and T can be used together with other
conditions as input to storm-surge models. Other conditions include boundary
conditions such as bathymetry, orientation of the coastline, etc. A storm-surge
model can be used to compute the surge heights at the coast. The storm surge
generated by a hurricane is the increase of the sea water surface elevation due
to two physical processes. One process is the water surface elevation increase
in the core region of a hurricane where the atmospheric pressure is extremely
low. This is the so-called "inverse barometer effect." The other process is the
convergence of the sea water, driven by the surface wind from the deeper ocean to
the shallower coastal regions. This is related to surface wind stress and
bathymetry. The atmospheric pressure gradient in a hurricane is the difference
between the central pressure and a peripheral pressure. The surface wind stress
in a hurricane is parameterized on the basis of the wind field near the water
surface. Using appropriate meteorological assumptions, a wind field can be
derived from knowledge of the pressure gradient, the radius of maximum wind
speed, and the forward direction and speed of the hurricane.
The joint probability approach, as currently used in storm-surge frequency
studies, assumes that each meteorological parameter used as input to the
hydrodynamical model is independent. Development of storm-surge probabilities
involves making computations for a range of meteorological parameters. The
probability of occurrence of a given simulation is assumed to be the product of
the probabilities represented by each input (meteorological) parameter. However,
if the meteorological parameters are interrelated, a simple product of the
individual probabilities is not appropriate. Hence, the need to evaluate the
possibility of interdependence among the factors that are the focus of this
study. With this specific application in mind, there were a number of decisions
made during the course of our analysis that ensured that the results would be
tailored to the needs of the hydrodynamic modeling application. Some examples
include the selection of the radius of maximum winds at the time of minimum
pressure, and the assumption that the parameters represented steady-state
storms. But these decisions also mean that the "climatology" described in this
report may not be appropriate for other more general meteorological applications.
1.5 Previous Studies
One of the first systematic compilations of the characteristics of hurricanes
affecting the United States coast was Tropical Cyclones (Cline 192 6). Table 1 in
Hydrometeorological Report No. 32 (Myers 1954) provided the first compilation of
all hurricane central pressures and radii of maximum winds from 1900 to 1949.
The National Hurricane Research Project Report No. 33 (Graham and Nunn 1959),
hereafter referred to as NHRP 33, updated Myers' list and systematized the
geographical distribution of the factors. Technical Paper No. 55 (Cry 1965)
described all the hurricane tracks from 1871 to 1963, and cited the earlier works
of this kind. HUR 7-97, Interim Report - Meteorological Characteristics of the
Probable Maximum Hurricane, Atlantic and Gulf Coasts of the United States
(Weather Bureau 1968) updated and revised the data in NHRP 33 and gave the
geographical distribution of the characteristics of hypothetical hurricanes that
had combinations of factors that made them the most severe hurricanes that can
probably occur at a particular coastal location. NOAA Technical Report NWS 23
(Schwerdt, et al 1979) revised and updated the previous studies on meteorological
criteria for engineering design hurricanes. Neumann et al. (1981) extended the
period covered in Cry's hurricane tracks and prepared revised tracks where
additional data indicated that they were necessary. This provided a firm
climatological base describing tropical cyclones on the synoptic scale.
2 . DATA
2.1 Introduction
Observations from hurricanes occurring near the United States Gulf and Atlantic
coasts were used in this study to determine probability distributions of various
parameters. Data presented in this chapter are used in later chapters of this
report. If additional data were required for a specific purpose, it is discussed
in the chapter where required.
The amount of observed data available from past hurricanes varies greatly and
almost all of it required further analysis and interpretation before it could be
of use for storm-surge computation. The amount of data available for any single
storm also varies during different portions of the storm's life, from various
geographic regions, and from different sections of the hurricane. These data are
subject to numerous uncertainties in interpretation. We have attempted to bring
this information together to make a comprehensive analysis, to develop accurate
storm tracks from which speed and direction of storm motion are determined and to
present an authoritative determination of central pressures and radius of maximum
winds. Examples of detailed meteorological analyses are given in Appendix A.
Tables 1 through 3, for hurricanes during the years 1900-84, list most of the
information used throughout this report. Parameter values in the tables are given
for storms with P Q less than or equal to 982 mb (2 9.00 in.) occurring within
150 nmi of the Gulf and Atlantic coasts. The data are our update, revision and
extension of Tables 1 and 2 in TR 15. There were a few changes made to the
previously published data. In particular, to address the question of
interdependence among parameters, available data were reviewed to ascertain their
time of occurrence and to provide concurrent values of P and R where necessary.
Tables 1 through 3 give the date at which a hurricane entered, exited or came
closest to the coast. The point along the coast where the hurricane parameters
may be applied is indicated in the tables as the coastal reference point. The
tables list parameters for the 85-yr period, 1900-84. The year 1900 was chosen
to initiate estimation of the parameters by weighing the inaccuracies that would
result from the sparse data of earlier years against the desirability of a longer
period. Each of the P and R values listed in the tables is followed by a
superscript letter or letters that refer to a legend at the end of the tables
giving the source of the data value. The storm direction, measured from the
north, denotes the track direction from which the hurricane crossed or bypassed
the coast.
Tables 1 and 2 list a storm twice only if it crosses the coastline a second
time (or if a bypassing storm makes another approach to the coast) after it has
traveled a distance of 400 nmi (500 nmi along the Gulf Coast). An exception to
this is Hurricane David: it was listed twice within 400 nmi, but only the second
entry was included in the statistical computations discussed below. These dupli-
cate storms are identified by a section mark (§) in the two tables. Hurricanes
whose centers passed through the Florida Keys are listed in both the Gulf and
Atlantic coast tables for the convenience of the user. The information on
hurricanes which crossed the Florida Keys and eventually entered the west coast
of Florida (within 500 nmi of its initial crossing), are listed separately in
Table 3A.
If a hurricane crossed the coast on one side of the Florida peninsula, with a
P less than or equal to 982 mb (29.00 in.) and weakened in intensity to
P greater than 982 mb when it was more than 50 nmi from the opposite coast, it
was listed for only the initial coastline it crossed (table 1 or 2). Those
exiting storms, still of hurricane intensity at, or within 50 nmi of, the coast
of exit, are included in Tables 1 and 2. Hurricanes which entered the Florida
coasts and moved northward over land maintaining hurricane intensity within
50 nmi of the opposite coast are listed separately in Table 3B. They may be
considered as bypassing hurricanes moving inland parallel to the coast.
2.2 Sources of Data
Original sources of hurricane data are barograph traces from land stations and
ships, wind records from NWS and military stations, aircraft reconnaissance
flight data, radar data, satellite data, miscellaneous pressure and wind reports
and textual descriptions in the scientific literature. These descriptions have
appeared in the Monthly Weather Review (published since June 1872),
Clima tological Data, National Summary (since 1950), National Hurricane Research
Project Report No. 39 (Graham and Hudson 1960), NOAA Technical Memorandum
NWS SR-56 (Sugg et al. 1971), the book Tropical Cyclones (Cline 192 6), and a few
other sources (e.g., data sources listed in append. A).
C S "O c
O k II O
C O t. u
-H 4J O C
en c uj to
Shut:
O HU
u o
3 3 T3
Z 3
r- o
Z 3
f~ o
Z 3
03 o <n
-h a u
u n v
a to u
a o
< o
3 S 3 4) -
CO e 0) -H to
01 O .* 0> M
U U TO 3 3
c u m a o
to .a e to >■>
rtTJU [i, > ffl
4) TO
B.H u - 01 BO
1- O O -H X- S
01 H S J *j
2 I
2 3
O CD
u a. c en
Z 01 00 o o
in o r-^ en —
-i —
x in
O iJ >
O. (0
— O r^ cm cm
oo u"» vo cr* r-~
2 3
to co m co cm —
co co to to . .
O o O o ir\ — .
Ov CO c-l O
01 o
O J I S
O fa N C
u e
05 C
18
O O
23
3 s
a) o
01
Si
00 cr* p~
en o o> — -3- -3-
0> ^J «h -T 0> 0>
— a\ o\ — . — i
MS vO
10
O U 14-1
U (0 <D
a. to u
a. o
u <u m <u -o m o
'» J «- '1) o c «
Z 3
oo o to
Z 3 Z 3
< ua u c£i u
11
O 3
O o
<u —
■ C3
3 in >s
to oo Ob
2 3 Z 3
vO CTv — c — i
<r -i — .o
fH <T\ "O 00 -H
aw u ^
12
u T) « u -D
U 0) O BO
B 3
C o
CO
O CO
Ail a
— i -* a.
Id S) -*
S It. >
03 -H
id a
55 2 Z 3 55 3
ra en CO O i*"- co 03 CM — .CO CO
o onu-icooo o -a- r^ o b
O CM CO CN ON CJ O N» U tl
ai a) a) a) o a) ai aj
CO E — O C-J
td.^d- C ^
13
a, -h —
to a.
> a
.a o to c u
o c to to
c o j to
« U C^li. DO
u v •* u u u
3 B 3 V - 3
X E 11 >H 10 0) 0)
« o^ g no tu to
u u to 3 3 by
c ^ j w a.
^ . U a)
i c a-o a)
3 — -h 01 >> 3 u
O CO .£ U u O O
j u to ei, a j u*
m a.
CM CfN ON
2 3 Z 3
■* — l«- O
vO O -3- —
Z 3
vD C^
Z 3
vO CD
Z 3
o o
14
a. ** — i
> a
a <-> -a a. u = u
o a a
th a u,
c -rt o
£ O :-l£ o
4J -- O
o >,
o 3
= 3
i>- o os
as — —
OS as OS
o o o o
OS — i OS
15
1 .- 3
= — 1 TJ <->
=
a js C w
3] -J) CO <0
o
l-> C-M <D
Q. U 11
u- c a.
.a to
u O 1 «
a -o o
e -M
<U C -H
u a.
3 to O >*-
o o
1) U u-
-J 3 O
en <->
(0 >
-a bo
TO c
t: o
ao 0> 3>
c u
c ai
to u
> u
o e u
a. u c <u
-* W 10 4J
oo a> a>
o o c
oo o o>
■j~. iz. en
16
Hi.
3 3 3 3
■0 X
O u
2 3 Z 3
ON — 1 -H (N
i/^ O in ifl
u c :
c *H -H
•h j= z
-I O C
Z 3 2 3
-3- m a- —
00 oc o o
jj w bO-w
17
CO
S
ei
a e
1
1
■o o
C ft.
-J
_
c
H -*
3
3
■*"
m
■o
0)
z
CD
CO >
vo
to u
in
3 1)
m
z
C
as -a
<3>
CU
o
2
OS
CU
as =
CD
o
m
c
m
■o
01 CD
3 u
(DO)
c
c
c
o. .C
o
o
o
O
o
o
CU
OS
ei
os
^
o
o
©
ft. B
cjn
a\
evi
~3-
d
cr\
av
on
? S
Z ?
Z 3
T3
© en
on m
CU cu
03 -.
en -t
O 00
C-J 00
to a
> a
TO
"7
%)
CU
^
c
O
c^
m
00
00
a.
^
o
O
o
B
O".
er\
cr\
cJn.
On
B •
u u.
o -.
m
o
C
u *a
ON
■*
C/5
~
rg
<N
". ^
X TO •
>v
>,
O u U
43
J3
J2
o. co u
-»
O
o. o
m
NO
< O
s
5
CD
00
00
lTI
ON
ON
on
- CU
on >-,
t— c
CD 0)
CO
CD.
CO
MQ
•u X
B0-->
3 ^
a.--'
<
CU
«cfi
■"
en
u a.
o o
in u
2 3 Z 3
00 <T ON O
On o no O
—CO
CU U
— • o
o « a
1 8
19
o «
M
S 3
s "S
- a
> =
O u <u
Ui 01 J)
emu
a o
< u
O 4J
to 52
3 «
CO XI (J
2 I
— xi on e
O O W
20
3 =
11
IS
1-
7 2
§1
1 S
3 u
u ij O 3 >U
3 a " JO
• g to u Hi
II 3 -VI -
CiJ <o
u o <o o.t-<j u iii ii a. -n Sum an n S
<g m to — I MO a aidicuo <u c C
a, u 3 co c a. -* u u .* o uu_i
4j«3 <n u ca -w Sco n u flo h u oiuroo
e 3 a tu — i c c o. cu s _j m i- -* « : s>m
OOE 3 CU -o -* O S 3 o (03 3U
> .3 co o .c cu -< :> O co ouu-u^rj O'-J'-mu
< « H _] JJ u <m < i/-| r_, JOOOO--' JOOO
S C
c a e
-< o
S C *J
= -o = -n
-> o s
C CO
o c
21
S 1
O O E
•u JJ c
c to
—I OJ <D O
■H O >, C
o h ii.a
m V
Q. 4J O !-
<4- fc. K
o bo
73 J= 00
O - !0 -J -H
a. a u
(0 4J 3
to jC
-I > C U
a 4-i •* a; u
a «j ao o 3
22
Tropical cyclone track information was used to determine the frequency of
entering, exiting, and alongshore tropical storms and hurricanes, direction of
forward motion and in some cases speed of motion. Smoothed best tracks have been
given in several NOAA publications and periodicals previously cited. Cry (1965)
combined data from available sources into a comprehensive report showing the most
accurate and consistent locations of all tropical cyclones for the period
1871-1963. These tracks were designed to provide a smoothed track for all
storms. Neumann et al. (1981) have extended the period covered and prepared
revised tracks where additional data have indicated they were necessary. In
addition, Jarvinen et al. (1984) have prepared a computer file of North Atlantic
tropical cyclones (commonly referred to as the HURDAT tape). This file contains
dates, tracks, windspeeds, and central pressure values (if available) for all
tropical cyclones that occurred during the period 1886-1983. This file is
maintained by the National Hurricane Center (NHC), NOAA, in Miami, Florida and is
updated annually. This data file contains storm positions and wind speed
information at 6-hourly intervals. They are subject to some degree of
uncertainty, especially for the earlier years. It should be noted that linear
interpolation of the data within 6-hourly intervals could lead to inaccurate
instaneous storm track and wind speed information.
2.3 Hurricane Central Pressure (P Q ) Data
The most important factor in storm surge modeling is the* intensity of the
hurricane, which is directly related to its central pressure. Harris (1959)
demonstrated that storm surge height is approximately proportional to the central
pressure depression, other factors being constant.
The specific pressure values in Tables 1 through 3 are the lowest pressures,
generally determined from actual observations by either a barometer or
dropsonde. For hurricanes of recent years, minimum pressure observed in
penetrations of the hurricane eye by reconnaissance aircraft near the coast
provided the central pressure in most cases. For earlier hurricanes, P values
were estimated from observations taken at land stations. Observed pressures, P ,
were extrapolated inward to P (since P were rarely observed at the storm
center) by using visually-fitted radial pressure profiles based on the formula
(Schloemer 1954):
P
" - exp(-R/r) (1)
P - P
n o
where P is the pressure at radius r, P
is the pressure at some large distance from the center at which the profile is
asymptotic, and R is the radius at which the windspeed is greatest.
Schwerdt et al. (1979) computed pressure profiles for 19 past hurricanes using
equation (1) and nine other pressure profile formulas and compared the results
with observed data at radial distances of 40 and 80 nmi. They concluded that
equation (1) gives a reasonably representative sea-level hurricane pressure
profile. They also concluded that further refinements would not improve the
reliability of the formula at this time because of the rather large scatter
of pressure data around most hurricane profiles.
23
2.3.1 Central Pressure Criteria Based on Balanced Wind Model
Tables 1 through 3 also list the lowest pressure observed at a station (P_),
the observing station and a geographical reference to which P pertains (either
at the coast or as far as 150 nmi offshore). The criterion used to select storm
data for inclusion in Tables 1 through 3 ( P <_ 982 mb) was based on consideration
of the windspeed computed from a balanced wind model (after Myers 1954):
where, V Q = cyclostrophic windspeed, at which the centrifugal
force exactly balances the horizontal pressure
gradient force at radius, r,
p = density of air,
P = asymptotic pressure (same as defined in eq. 1),
R = radius of maximum winds.
At the radius of maximum winds (R=r), with a central pressure of 982 mb
(29.00 in.) and an asymptotic pressure of 1015.9 mb (30.00 in.), the
cyclostrophic windspeed is 73 mph, or about the windspeed required for
classification as a hurricane. The asymptotic pressure used by Myers is
different from the peripheral pressure suggested in Chapter 11. Both pressures
are intended to be representative of the environment removed from the dynamics of
the tropical cyclone; Myers' pressure is that value to which an exponential
pressure profile defined by equation 1 is asymptotic. It is a parameter for
defining the intensity of the pressure gradient and does not actually have a
physical counterpart in the pressure field. The peripheral pressure used in this
report is the surface pressure at the outer limit of a hurricane where the
cyclonic circulation ends and, therefore, has a physical meaning. The 982-mb
criterion was used to put a specific bound on the data sample. We realize that
there have been storms with hurricane-force winds and central pressures higher
than 982 mb south of 3 5°N. It is not intended to be used as a forecasting
criterion to distinguish hurricanes from tropical storms.
2 .3 .2 Central Pressure Adjustments
In some areas, barometric pressures could not be obtained near the coast. The
central pressures were determined at the location nearest the coast where
reliable observations could be obtained and adjusted downward to a coastal
value. This was done for those central pressures for which the lowest observed
pressure was from a station inland or at a coastal station when the storm was
emerging from land to sea. These adjustments were made for 13 hurricanes and
were carried over from TR 15 and earlier reports, including NHRP 33.
Recomputations using filling rates given in Chapter 10 did not show significant
differences; P values for 3 of 13 hurricanes were revised.
24
Questions have been raised about the minimum central pressure of Hurricane
Camille which struck the northern Gulf coast in 1969. The best obtainable value
is needed because Camille had the lowest central pressure on the mainland coast
since record keeping began during the later part of the last century, and
stronglv influences the lower end of the probability distribution of central
pressure. A minimum pressure of 905 mb was measured by an Air Force
reconnaissance aircraft at 0016 GMT on August 17, 1969 near 25.2°N, 87.2°W, or
250 mi southeast of the mouth of the Mississippi River. Eighteen hours later,
and only a few hours before the center made landfall, another reconnaissance
aircraft penetrated the hurricane, and reported an even lower central pressure of
901 mb. A post-audit of the dropsonde computation at the National Climatic
Center adjusted this to 908 mb. This value, which is quoted by Bradbury (1971),
is the value in Table 1. The eye passed over Bay St. Louis, Mississippi, at
landfall and an aneroid barometer a few blocks from the west end of the Bay
St. Louis-Pass Christian bridge read 2 6.85 in. (909.4 mb) . This barometer was
later checked and found to be accurate by the New Orleans NWS Office (DeAngelis
and Nelson 1969). One may assume then that Camille remained in a near steady
state during its last 25 hours at sea.
2.3.3 Revised Central Pressure from Previous Studies
A virtual absence of pressure data made it necessary to omit the Louisiana hur-
ricane of August 6, 1918, in which the closest recorded pressure was some
90 nmi from the path of the storm center. An estimate of P from such a
distance would be highly questionable. Two hurricanes listed in NHRP 33 are not
included in Tables 1 through 3. Upon reanalysis of the data, it was decided
that both had weakened' to tropical storm strength before they reached a point
50 nmi from where they exited the Florida coast. They are the storms of
September 11, 1903 (Gulf coast) and October 20, 192 4 (Atlantic coast).
On the basis of additional data discovered since the 1975 study, we revised
the central pressure for several hurricanes. The most significant change
involved the storm of September 20, 1909. The revision was based on a
reconsideration of records available from the Weather Service Forecast Office in
New Orleans. A few other changes of central pressures were made in hurricanes
whose radius of maximum winds were revised. A recomputation using the pressure
profile formula with the revised R values dictated these revisions. The dates of
these hurricanes, and their previous and revised central pressure values are
listed in Table 4.
2.4 Hurricane Radius of Maximum Winds (R) Data
Values of R for hurricanes were derived from various sources for the Gulf and
Atlantic coasts of the United States. In TR 1 5 the values of R were for
arbitrary locations and times. In this study, we reviewed all available data and
determined concurrent values of P and R. The R values listed in Tables 1
through 3 are derived near the location and time where P applies. With aerial
reconnaissance data, the R values are obtained from wind data recorded during the
same traverse of the storm center in which the minimum P was observed. In a few
cases, R could not be obtained by any reliable method. Storms with R's in this
category are represented in Tables 1 through 3 by the abbreviation MSG (missing).
25
Table 4. — Hurricanes with revised central pressure
Gulf
Previous
Revised
Date
P o
P o
(mb)
(mb)
Oct. 18, 1906
976.6
966.8
Sept. 20, 1909
980.0
965.1
July 5, 1916
961.1
950.2
Nov. 5, 193 5
972.9
977.0
Oct. 5, 1948
977.0
962.7
Sept. 10, 1960
(Donna)
933.0
93 0.0
Sept. 15, 1960
(Ethel)
972.0
976.0
Date
Atlantic
Previous Revised
(
3
(mb)
(ml
O
Sept.
17,
1906
981.4
976
.6
Sept.
18,
1926
93 4.3
93 1
.0
Aug.
23,
1933
969.5
966
.5
Sept.
21,
1938
939.7
943
.0
Sept.
15,
1944
958.7
955
.3
Sept.
17,
1947
940.1
946
.8
Aug.
28,
1958 (Daisy)
957.0
949
.0
Sept.
12,
1960
(Donna)
961.1
959
.0
Sept.
10,
1964
(Dora)
965.8
961
.0
2.4.1 Source of Radius of Maximum Winds
The values of R in the tables were developed from several sources: 1) windspeed
records from aerial reconnaissance (for hurricanes since 1947), 2) windspeed
records from land stations, whenever applicable, 3) approximations of eye radii
deduced from airborne or land-based radar, 4) computations from an estimate of
the pressure profile, or 5) on the basis of narrative or tabular data in the
Monthly Weather Review.
2.4.1.1 Radius of Maximum Winds from Aerial Reconnaissance. Maximum flight-
level winds and estimated maximum surface winds are usually included in flight
reports from reconnaissance aircraft. Flight-level winds, recorded at one-second
intervals by N0AA research aircraft flown into hurricanes have also been
available since 1953. Recorded flight-level winds were processed and 10-second
averages are stored on microfilm for data prior to 1973 and on magnetic tapes for
recent years. Wind and pressure data on microfilm were tabulated, plotted, and
analyzed for hurricanes affecting the U.S. coasts. From magnetic tape records
since 1973, composite maps of flight-level winds relative to the storm center at
given intervals and winds at various radial distances from the storm center
recorded in a traverse through the eye were plotted by computer and made
available to us by the Hurricane Research Division (HRD) of the Atlantic
Oceanographic and Meteorological Laboratory (AOML) of NOAA. Analyses of these
maps yielded another measure of the radius of maximum winds. Examples of these
analyses are given in Appendix A.
It is generally accepted that, above the boundary layer, there is little
vertical shear in a hurricane windfield in the lower troposphere (below about
600 mb). Miller (1958) developed a 3-dimensional description of the windfield in
a tropical cyclone. Shea and Gray (1972) found that only the weaker storms
exhibit a tendency for a slope of the radius of maximum winds with height; more
intense storms do not. Willoughby et al. (1982) analyzed multi-level (1,500,
5,000 and 10,000 ft) flight data in Hurricane Allen (1980) and showed that
26
50
45
40
35
^
-
30
'"'
o
LkJ
RS
■jA
.n
20
2
3
15
10
OBSERVED WIND SPEED
3
00
OS
i 2
00
00
TIME CGMT5
7igure 2. — Hourly observations of wind speed and direction, and distance of
Allen's center from Brownsville, Texas for period 1300 GMT on August 8 through
0600 GMT on August 11, 1980.
the magnitudes of the maximum winds at different flight levels were generally
quite similar. We concluded that flight-level wind data recorded at altitudes
below the 600-mb level can be used to determine the surface value of R in
hurricanes of moderate or greater than average intensity. Examples of this
method of obtaining R are given in the data analysis in Appendix A.
2.4.1.2 Radius of Maximum Winds from Wind Records. Observed maximum winds are
determined by noting the time when a wind-reporting station experienced the
highest windspeed prior to the wind slackening in the hurricane's eye. From a
knowledge of the location of the storm center at that time, one can deduce a
value of R. Similar results can be obtained from various types of wind
recorders. The windspeeds read off anemometer records were plotted on a time
scale and a smooth curve drawn. A curve of distance from the storm center, as
measured from the best track, was constructed on the same time scale. The two
curves are shown for Hurricane Allen (1980) in Figure 2. The two peaks in the
wind graph indicated that the storm's track took the center closer to the station
than the radius of maximum winds. The 'observed' radius of maximum winds would
27
be the distance from the wind center at the time of these peaks. If the track
had kept the storm center beyond R, there would have been only one peak in the
wind profile. In this case, it was established that the radius of maximum winds
was less than the distance of station from the storm track.
2.4.1.3 Radius of Maximum Winds from Eye Radius. In their work, The Structure
and Dynamics of the Hurricane's Inner Core Region , Shea and Gray (1972) stated
that, in the mean, the radius of maximum winds occurs at radii 5 to 6 nmi outside
the inner radar eye radius (IRR) - assumed synonymous with the inner cloud
wall. The IRR may be obtained from land-based radar, ships at sea, or
aircraft. Figure 3, taken from Shea and Gray, shows the position of R relative
to the IRR for 2 1 Atlantic Ocean and Gulf of Mexico hurricanes. Figure 4, also
from Shea and Gray, shows the difference between R and IRR versus the maximum
windspeed for radial flight legs. Note that the more intense the wind the better
the agreement between R and IRR.
2.4.1.4 Radius of Maximum Winds from Pressure Fit. Computed R's can be
estimated by fitting an exponential pressure profile to the data from a given
hurricane. By their nature, computed values of R are more subject to error than
observed R's. The procedure was used in previous studies to derive estimates
that were carried over into the present study and was discussed by Myers (1954).
2.4.1.5 Radius of Maximum Winds from Monthly Weather Review . Reports of radii
of maximum winds extracted from storm analyses in the Monthly Weather Review
usually consist of estimates of the diameters from the measured time interval
between the slackening and resumption of hurricane-force winds over some
point near or along the coast. In other instances, researchers have reported
their findings in the Monthly Weather Review , and these results (including
estimates of the radius of maximum winds) have been accepted by the authors of
this study.
2.5 Speed (T) and Direction (9) of Forward Motion
The translation speed and direction of hurricane motion are, among others,
important factors for determination of storm surges along the open coast.
Forward speed and direction were determined primarily from analysis of hourly
hurricane positions when they were available. Generally, the analyses of
meteorological data are weighted toward synoptic-scale motions. The hurricane
track, thus obtained, is a best estimate of the large-scale storm motion and not
a precise location of the eye at discrete time intervals. In this report,
direction of storm motion is measured clockwise from north and denotes the
direction from which the storm crossed or bypassed the coast.
2.5.1 Source of T and 8 Data
The T and 9 information in Tables 1 through 3 were extracted from storm track
charts. Hurricane tracks compiled by Cry (1965) and the charts for recent years
published by the NHC, NOAA, in Miami, Florida (Neumann et al. 1981, and Jarvinen
et al. 1984) were used. The speeds were derived mostly from detailed track
charts, depicting hourly or bi-hourly positions in the vicinity of the coast,
such as: Myers (1954), Graham and Hudson (1960), and Ho and Miller (1982,
1983). The listed T and 8 pertain to the time of landfall, exit, or closest
approach to the coast. In Tables 1 through 3, both the T and 9 data prior to
1973 were carried forward from Tables 1 and 2 of TR 15.
28
Figure 3. — Radius of maximum winds (R) versus inner radar eye radius (IRR).
Points falling on the 45° line are Chose where the R and IRR coincide- The
curved line indicates the best fit curve (from Shea and Gray 1972).
a: ic- S
I
' •
- 1
•
- 1
•
<
•
•
•
i*i
•
_ 5
•••
• • •
•
a
•
~ 3
•
•
:
• •
•
— d
• • • • •
_ UJ
•
9 •
•
£;
••
•••••• •
• •
_ a
• •
.•!•: •* $
• ••• •
•/)
•
• • • •
_ z
•
v*
•^^_^ • * ••• •
•• • • / •• •
2
• • •
X
• • •
•
— *
•
. ..37f>4c
^ m*t — •
_
.
-1 (
%'"
•1 :"•%*•. •*** «f
^**><*f^
•
- NO DIFFERENCE
...,:« # •.
'.'jVV h » r 1 ■
L« * ••••••••• t 3
•
• •"* • •'
IRR
_
-
• •
• • • . •
30 SO ICC
MAXIMUM WIND SPEED !
Figure 4. — Difference between the radius of maximum winds (R) and the inner radar
eye radius (IRR) versus maximum wind speed. The best fit curve is indicated by
the heavy line (from Shea and Gray 1972).
29
2.5.2 T and 9 Data Used in Probability Distributions
In our present study, cumulative probability curves for T and 9 were plotted
for tropical cyclones since 1900. In TR 15, T data for hurricanes since 1886
were used in the plots. We made similar analyses using hurricane data from 1900-
84 and found little difference in the results.
To expand our data sample for speed of forward motion, we utilized T data from
all tropical cyclones landfalling on the Gulf and Atlantic coasts. In addition
to the T data for landfalling hurricanes listed in Tables 1 through 3, average
speeds for weaker storms were estimated from 6-hourly positions given on the
HURDAT tape (Jarvinen et al. 1984). We chose the average speed, computed at
synoptic hours, closest to the time of landfall as an approximation for
landfalling tropical storms.
Directions of landfalling tropical cyclones were determined at the times they
crossed the coast. In TR 15, the sample of 9 included values from hurricanes and
tropical storms since 1871. In the present study, 9 data came from tropical
cyclones that occurred during the 85-year period, 1900-84.
3. METEOROLOGICAL PARAMETERS AND THEIR INTERRELATIONS
3.1 In t r oduc t ion
Meteorological parameters used in the hurricane climatology analysis are
central pressure (P Q )> radius of maximum winds (R) , forward speed (T) and
direction (9) of storm motion. Since the computation of storm-surge frequencies
using the joint probability approach assumes independence among the parameters,
any interdependencies must be identified and taken into account.
In addition to the basic hurricane parameters, location parameters include a
coastal reference milepost (m), the latitude (0) and the longitude (X). The
mileposts are assigned such that m = at the Mexican border and increases along
the Gulf coast toward Florida, reaching a value of 1415 at the southern tip of
Florida. The value of m further increases northward along the Atlantic coast to
m = 3100 at the Canadian border (see fig. 1).
3.1.1 Overview of the Statistical Study
The ultimate purpose of the statistical tests was to find interrelations
between the hurricane parameters, if any, so that those parameters could be
properly accounted for in the storm-surge frequency computations. Because of
large natural variability, our data sample did not provide a sufficient number of
storms to estimate the underlying populations over coastal segments short enough
to allow homogeneity to be assumed a priori. This made it desirable to pool data
over as large an area as possible, to increase reliability of population
estimation and hypothesis testing. However, the pooled data could only include
coastal segments that were both statistically and meteorologically homogeneous.
While determination of meteorologically homogeneous coastal segments was, of
necessity, somewhat subjective, we complemented our judgments with consideration
of statistical homogeneity. We felt that the variability in the data and limited
sample sizes precluded a purely statistical determination of homogeneous regions.
30
The statistical methods used in this chapter are outlined in Appendix B,
wherein the rationale for their choice, their limitations, and the interpretation
of the results are discussed. We used two methods to delineate regions in which
the hurricane parameters might be considered homogeneous: a meteorologically
based method and a statistical method (based on cluster analysis).
For the meteorological method, hurricanes that struck a coastal segment that
had relatively uniform orientation were grouped together. We then performed
tests to determine whether the statistical characteristics of hurricane
parameters among the various groupings were similar. The groups with no
significant differences in statistical characteristics were considered for
combination into a larger group. These pooled groups provided larger sample
sizes for tests of interrelations between hurricane parameters.
We also performed a cluster analysis on the parameters of all hurricanes
located along Gulf and Atlantic coasts; the hurricanes were separated into
clusters (groups) based upon the characteristics of the sample data. The groups
of hurricanes so obtained were then examined using principal component analysis
and discriminant analysis to determine whether significant differences existed
between the groups. The results were compared with those of the meteorological
method.
3.1.2 Scope of the Chapter
In Section 3.2, a comparison of the statistical characteristics of forward
speed of hurricanes and tropical storms Is discussed. Practical problems with
the treatment of the direction of motion of landf ailing hurricanes and tropical
storms is also discussed in this section. The homogeneity of hurricane
parameters from different geographical regions is discussed in Section 3.3. The
results of homogeneity test were used as guidelines for pooling the data samples
used in the independence tests. In Section 3.4, interrelations between hurricane
parameters are examined. In Section 3.5, the interdependence between hurricane
parameters is discussed, and our conclusions are presented.
3.2 Considerations of Data Samples for Statistical Tests
Tropical storm data included forward direction and speed for the Gulf and
Atlantic coasts of the United States. Central pressure and radius of maximum
winds for individual tropical storms could not be adequately specified. However,
central pressures of all tropical storms are, by our definition (see sec. 2.3.1),
greater than 982 mb. Only landfalling tropical storm data were considered.
The landfalling tropical storm data were separated into two groups: one for
the Gulf coast and the other for the Atlantic coast. For comparison, the
landfalling hurricane data were also separated in the same manner. To examine
whether the distributions of landfalling hurricanes and tropical storms should be
considered separately, we set up the following data subsets:
GH: landfalling hurricanes on the Gulf coast,
GT: landfalling tropical storms on the Gulf coast,
AH: landfalling hurricanes on the Atlantic coast, and
AT: landfalling tropical storms on the Atlantic coast.
31
Table 5. — Forward speed of hurricanes and tropical storms for selected portions
of the coast
Type of Sample Average Speed ~ Standard Deviation
Storms "Size (kn) (kn)
___ West coast of Florida (1050 <_m <1415 nmi) —
Hurricanes 13 10.5 " 3.6
Tropical storms 28 15.8 7.6
Northern Atlantic coast (m > 2 400 nmi)
Hurricanes 7 34.7 7.8
Tropical storms 12 22.8 6.7
We performed the (1) Mann-Whitney test, (2) Wilcoxon two-sample test with
normal approximation, and (3) Kruskal-Wallis test with Chi-square approximation
on the data set pairs GH and GT, and AH and AT. Part of the Mann-Whitney test,
and all of the Wilcoxon and Kruskal-Wallis tests were conducted using SAS
procedures.
3.2.1 Forward Speed
The results of the three tests show no significant difference between the
distributions of landfalling hurricanes and landfalling tropical storms for
either the Gulf or Atlantic coasts. We also inspected scatter diagrams of
forward speed vs. railepost for landfalling hurricanes and landfalling tropical
storms. Figures 5a and 5b show that the distribution of forward speed of
landfalling hurricanes and tropical storms for the west coast of Florida
(m = 1050-1415) differs from that for mileposts greater than. 2400. The latter is
located north of Chesapeake Bay. Table 5 shows that tropical storms that struck
land, on average, moved faster than did hurricanes along the west coast of
Florida, but moved more slowly than hurricanes for the northern portion of
the Atlantic coast. The variation along the Florida coast appears to be
reasonable, and is explained by the fact that storms that recurve tend to move
faster as they become embedded in stronger westerly flow. Strong westerlies also
tend to disrupt the delicate thermal circulation necessary to support intense
storms. Therefore, storms that recurve tend to be weaker (tropical storms)
and move more rapidly. We concluded that hurricanes and tropical storms in this
area represented complementary portions of the same distribution, not separate
distributions.
Clearly, the observations north of milepost 2 400 cannot be explained this
way. While we have no fully satisfactory explanation for what the data indicate,
we note that the sample size is rather small, and for the hurricanes, the
variability is considerably higher than the Florida sample (see table 5).
Furthermore, most storms, whether hurricanes or tropical storms, that reach
SAS is the Statistical Analysis System. Mention of a commercial product does
not constitute endorsement by the Federal Government.
32
050 1100 1200 1300 I 400 "500
MILEPOST Cnmi)
* Hurricanes
• Tropical Storms
30
-
— r
#
> i i
r- T" " r 1
1 1
(b)
40
*
*
-
30
-
•
*
*
•
•
a
LU
Q.
20
10
"
•
*
•
•
•
• •
•
•
2400 2500
^ Hurrfeanvt
• Trojteal 3torm«
2600 2700 2800 2900
MILEPOST Cnmi)
3000 3100 3200
Figure 5. — Forward speed of landfalling hurricanes and tropical storms versus
adlepost (a) along the Gulf coast of Florida, and (b) along the Atlantic coast.
33
these northern latitudes are moving quite rapidly. They appear to have been
transformed into systems whose circulations have extratropical characteristics.
The fastest moving storms are probably propagating as waves along a baroclinic
zone. Because of the small sample size, the generally large variability and the
indication that the dynamics of the storms north of milepost 2400 appear to be
quite unlike classical tropical cyclones, we exercised judgment in our analysis
of these data. We felt that the best estimate of the underlying population could
be achieved by consideration of the forward speed of both hurricanes and tropical
storms. Based upon the test results and on our judgment, we treated the speed of
motion for tropical storms the same as for hurricanes for both the Gulf and
Atlantic coasts.
3.2 .2 Forward Direction.
The data only include landf ailing storms. In our data sample, landf ailing
hurricanes outnumber hurricanes in the other categories (bypassing and exiting)
by a large amount. The sample sizes in the bypassing and exiting categories are
so small that it would not be possible to make meaningful inferences based on
statistical analysis.
Landfalling tropical cyclones are defined as those that strike the coast, hence
their range of forward directions is limited by the coastal orientation. The
range of directions can vary greatly as the coastal orientation changes over
short distances. This variation can limit the range of directions in the
category of landfalling storms in a way totally unrelated to real meteorological
variability. For this reason, we decided that it was not appropriate to treat
direction of motion as a random variable for the purposes of hypothesis testing,
and in particular, for examination of interrelations with other parameters.
Possible interrelations between 9 and the other hurricane parameters will be
considered further in Chapter 5.
3.3 Homogeneity of the Hurricane Data Samples
For the purposes of this study, homogeneity for a given coastal segment means
that parameter estimates from a sample of storms for one location appear to be
drawn from the same population as the parameter estimates for any other location
in the segment.
We separated the storms into groups so that each group consisted of the storms
that made landfall on a coastal segment that had relatively uniform orienta-
tion. Presumably, if the segment was properly selected, the data would be
meteorologically homogeneous. We then performed statistical tests to determine
whether the frequency distribution of the parameters from one group appeared to
be the same as other groups. The groups which appeared to show no significant
difference in their distributions were considered for combination into a larger
group.
Cluster analysis of the parameters provided another method to separate the
hurricanes into groups based on the characteristics of the data sample. The
groups of storms so obtained were tested using principal component analysis and
discriminant analysis to determine whether they appeared to be reasonable
partitions. The results were then compared with those of the meteorological
method (based on coastal orientation).
34
Table 6. — Initially selected coastal segments
Segment
Number
Number of Milepost Range
Hurricanes (smoothed coastline)
Description
23
0-400
Gulf coast from Mexican
border to Galveston, Texas
400-700
700-1100
Gulf coast from Galveston,
Texas to Mississippi delta
Gulf coast from Mississippi
delta to Suwannee Sound,
Florida
12
1100-1415
Gulf coast from Suwannee Sound,
Florida to the southern tip of
Florida peninsula
1415-1800
1800-2200
Whole Atlantic coast of Florida
Atlantic coast from Georgia to
Cape Hatteras
22 00-2 700
2 700-3100
Atlantic coast from Cape
Hatteras to Rhode Island
Atlantic coast from Rhode Island
to Canadian border
3.3.1 Methods for Testing the Homogeneity of Storm Parameters
In the meteorological method, we first selected eight segments along the Gulf
and Atlantic coasts of the United States. These eight segments were located in
the milepost ranges shown in Table 6 and are shown schematically in Figure 6 (see
also fig. 1). The number of landf ailing hurricanes in each segment is also
listed in Table 6.
There were four segments on the Gulf coast and another four segments on the
Atlantic coast. Milepost 1415 is located at the southern tip of Florida. Along
each segment, the orientation of the coastline is relatively uniform, except for
the two most northern segments along the Atlantic coast. For the first six
segments we used the Mann-Whitney test to examine the relation of P , R, and T
among pairs of segments. Segments 7 and 8 were not included in the testing
because of the small numbers of observations. The test was used to determine
whether the distribution functions of a given parameter appeared to be
significantly different between two segments of the coastline. If no difference
in distribution functions for two segments was detected for all parameters, those
two segments could be combined if the meteorological conditions in each segment
were deemed to be similar enough.
The seven parameters used in the cluster analysis were P , R, 0, T, the
milepost value (m), the latitude (0), and longitude (A) of the landfalling
point. For each grouping, principal component analysis and discriminant analysis
35
1 I I 1 [ 1 I I 1 I 1 1 I I
GULF COAST
I I I | J I I I
ATLANTIC COAST
Ml!
12 3 4 5 6 7 8
COASTAL SEGMENTS SELECTED INITIALLY
RESULT OF MAM-WHITNEY TEST
1
4
|
2
3
|lllll
5
illiij
!*: :
t$
&**>**&:']
RESULT OF CLUSTER ANALYSIS (? , R, 9 , T , n, , k )
o
'
>
1
\ \
LOCATIONS OF FREQUENCY MINIMA
GLF C ATL A
COASTAL SEGMENTS SELECTED FOR INDEPENDENCE TESTING
GULF COAST | ATLANTIC COAST
t I 1 I I I I 1 I I 1 1 1 I 1 1 1 1 1 I I I 1 I I 1 1
I I
5 10 15 20 25 20
MILEPOST (100 nmi)
Figure 6, — Possible homogeneous regions for landf ailing hurricane parameters.
Shaded areas have Insufficient or no data.
36
Table 7. — Results of Mann-Whitney test for a priori selection of coastal segments
in the Gulf of Mexico
Segment Segment Number
Number 12 3
Segment Number
1 2 3
Segment Number
1 2 3
*
* *
*
*
Segments as given in Table 6
* indicates segments with similar distributions
indicates segments with different distributions
were used to examine the similarity between the groups. The most distinctively
separated groups were selected and the parameters within each group were examined
for possible interrelations.
3.3.2 Comparison of Results from Different Homogeneity Tests
3.3.2.1 Meteorological Method. After the coastal segments were selected
(table 6), the Mann-Whitney test (Conover 1971) was performed to compare pairs of
segments. Adjacent segments with no significant difference in distribution
functions were considered for combination.
The results for the Gulf coast are shown in Table 7. In all cases, adjacent
segments appeared to have similar distributions. However, for P and T, some
segments that were separated by one or two segments appeared to come from
different distributions. For instance, for both parameters, segments 1 and 3 had
different distributions, even though they both had distributions similar to that
of segment 2. To explore the variation along the Gulf coast further, we divided
the data sample into different segments. An example is shown in Table 8, where
only 3 segments were used. Again, all segments appeared to have similar
distributions of R, but different distributions of P and T. Our analysis of
shifting the segment boundaries led us to conclude that the data appear to be
Table 8. — Results of Mann-Whitney test for modified segments of the Gulf coast
Segment
Number
P
o
Segment Number
1 2
R
Segment Number
1 2
T
Segment Number
1 2
Milepos t
Range
1
2
3
*
*
* *
* *
0-500
500-1000
1000-1415
* indicates segments with similar distributions
indicates segments with different distributions
37
"locally homogeneous." It appears that there may be variations along the
smoothed coastline in the Gulf that could result in samples that would not be
homogeneous if the segments were too large. However, it is not clear what "too
large" is. By that, we mean that the variation appears continuous and that
there are no obvious breakpoints between homogeneous regions. Therefore, the
data can be considered homogeneous locally. In Section 3.3.3, we combine this
with an evaluation of the statistically based cluster analysis to specify
homogeneous segments for the independence testing.
The concept of local homogeneity was also assumed to apply for the Atlantic
coast. As indicated in Table 6, the number of storms beyond milepost 2200 was
too small to consider formal statistical testing. The results of the Mann-
Whitney test for the region south of milepost 2200 were variable, depending on
the segments chosen. However, the results were not inconsistent with the concept
of local homogeneity. This Is reasonable, considering the known variation of the
hurricane parameters with latitude.
3.3.2.2 Cluster Analysis. The results of the cluster analysis were generally
consistent with the results of the meteorological method. In application of the
cluster analysis procedure, the number of clusters was assigned a priori, and the
cluster boundaries were then determined. Analyses for two through nine clusters
were conducted. When five clusters were selected, the partitioning was most
similar to that determined by the meteorological method. The cluster analysis
technique assigns each storm to a particular cluster and assigns it an
identification (ID) number. These ID numbers are shown in the schematic in
Figure-6. Somewhat surprisingly, each of the clusters included storms that
struck land over a continuous extent of the coast. That is, milepost alone could
be used to totally delineate which storms were included within each cluster.
This is consistent with our judgment used in specifying regions by the
meteorological approach (sec. 3.3.2.1). The cluster boundaries for the
five-cluster partition were generally located in regions of storm-frequency
minima (see fig. 27). Because of this, the last storm in one cluster (largest
milepost value) could be at a considerable distance (40 nmi or more) from the
first storm in the adjacent cluster. With this in mind, a cluster boundary in
Figure 6 should be considered a point somewhere in the transition region -
cluster boundaries are not precise delineations.
3.3.2.3 Discriminant Analysis. To determine how well the clusters of hurricanes
were separated, discriminant analysis was performed on them. In addition to
providing the seven parameters mentioned in Section 3.1 (P , R, T, 9, m, 4>, A), a
cluster identification number (as shown in fig. 6, for a 5-cluster partition) was
also used as input to the procedure. The results showed that hurricanes were not
distinctively separated by the cluster analysis for 3 through 9 clusters. For
example, in the case of five clusters, Hurricane Hazel of 1954, which made
landfall at milepost 2 077, was put in cluster 3 by the cluster analysis but
classified into cluster 1 by the discriminant analysis. In this case, cluster 1
includes hurricanes which made landfall in the milepost range 1-500 and cluster 3
includes those in the milepost range 1752-2294. The discriminant analysis and
the cluster analysis agree only on classifying all landfalling hurricanes into
two clusters: one Includes those in the milepost range 1-1201 and the other in
the milepost range 12 92-2 750, with missing data outside of these ranges. However,
38
Table 9. — Percentages of variance accounted for by principal components
Cumulative
Principal Percentage Percentage
Component of Variance of Variance
1 44.6 44.6
2 15.2 59.8
3 14.3 74.1
4 12.2 86.3
5 9.0 95.3
6 4.5 99.8
7 0.2 100.0
examining these milepost ranges, we felt that these two clusters cannot be
meteorologically homogeneous, especially the second cluster, because it includes
hurricanes which are generally larger in size and faster in forward motion as
compared to hurricanes in the lower latitudes.
3.3.2.4 Principal Component Analysis. Principal component analyses were
conducted to examine the relative importance of the parameters. The percentage
of variance that each principal component accounted for is shown in Table 9. The
first principal component accounts for almost 45 percent of the total variance,
and each of the next three principal components account for more than 12 percent
of the total variance. "Loadings" provide a measure of the contribution of the
parameters to each component. The loading of the hurricane parameters in the
four most significant principal components is shown in Table 10. Each column in
the table is an eigenvector normalized to have a unit length. This means that
the square root of the sum of squares of numbers in each column is unity.
Table 10 shows high positive loadings on the milepost (m) and landfalling
latitude (0) and high negative loading on the landfalling longitude (A) in the
first principal component, and high positive loading on central pressure (P.) in
the second principal component. The loading and importance of the first
component confirms our meteorological judgment that location is an important
factor in delineating homogeneous regions.
Table 10. — Loading of hurricane parameters in the principal components which
account for more than 12 percent of variance
Principal Component
Parameter 12 3 4
" F 07l3 0787 =0TT4 -0.16
R 0.31 0.33 0.11 0.60
9 0.20 0.13 0.73 -0.57
T 0.39 -0.28 0.39 0.26
-0.2 1
0.25
0.34
0.13
0.87
-0.14
0.31
0.33
0.11
0.20
0.13
0.73
0.39
-0.2 8
0.39
0.50
-0.14
-0.38
0.47
0.01
0.11
•0.48
0.14
0.3 6
39
■ I .
2
■3
*
t
ii
, !
1
1
*
<t««2 »
3
1
3
3
i
"»
• » 2
3
3
3
;
1
1
... .-
%
-h._?:!\
3
3
3
3
:
1
2
"»Ji
3
.
2
212
• »a »
3
3
2 2
2
♦
i
•
33
-3.6
•2.4
.2
0.0
1.2
2.4
3.6
4.8
Figure 7. — Plot of the second principal component versus the first principal
component. Each symbol represents a landfalling hurricane and indicates Che
cluster to which it belongs.
Using the classification provided by the cluster analysis, the second principal
component was plotted versus the first principal component as shown in
Figure 7. In this graph, each symbol represents a landfalling hurricane and the
symbol indicates the cluster to which it belongs. The figure shows that
clusters 1, 3, and 5 are distinctively separated with few "misclassif ications,"
and clusters 2 and 4 are mixed. Cluster 2 includes landfalling hurricanes in the
milepost range 1292-1584 which covers the southwest and southeast Florida
coast. Cluster 4 includes landfalling hurricanes in the milepost range 560-1201
which covers the Gulf coast from eastern Louisiana to the Florida panhandle.
Thus the landfalling hurricanes in the milepost range 560-1584 are difficult to
classify into distinctive subgroups on the basis of principal component
analysis. Note that location parameters played an important role in the first
component, and ? in the second component (see table 10). Figure 8 is a scatter
diagram showing the distribution of ? as a function of milepost for clusters 2
and 4. While there are fewer landfalling storms for mileposts 1000-12 50, the
range of pressures does not indicate any obvious clustering. In both the western
and eastern portions, most P 's range upwards from 930 mb, with an intense storm
in each section. It seems reasonable to group these data together on the basis of
the characteristics of their pressures.
3.3.3 Selection of Hurricane Groups for Independence Testing
The fact that the location parameters play an important role both in the prin-
cipal component analysis and in the cluster analysis supports our use of coastal
segments for the delineation of homogeneous regions of hurricane parameters. Con-
sideration of meteorological factors and the results of the statistical analysis
suggest boundaries between milepost 400-700, 1000-1200, 1600-1800, 2200-2300 and
near 1415. Milepost 1415 is chosen as a boundary because it is a dividing point
between the Gulf and Atlantic coasts. Tne regions we ultimately judged to be
homogeneous are summarized in Table 11 (see also fig. 6).
40
Table 11.— Coastal segments that include homogeneous hurricane parameters for the
test of independence
Segment
ID
Mile post
Range
Description
GLF
A
0-4 50
GIF
3
450-1050
GLF
C
1050-1415
ATL
A
1415-1800
ATL
B
1800-2 300
ATL
C
2300-3 100
Texas coast
Gulf coast from Louisiana to Florida Panhandle
West coast of Florida south of 30°N
East coast of Florida
Atlantic coast from Georgia to North Carolina,
including Cape Hatteras
Atlantic coast from Virginia to Canadian border
••
900 1 000 ! 1 00 1 200
MIL£P0ST CnmiD
Figure 3.— Central pressure of landfalling hurricanes versus atLlepost.
41
3.3.3.1 Gulf Coast. Both our meteorological judgment and statistical analyses
suggested that the region along the coast of Texas could be considered meteoro-
logically homogeneous. Our initial boundary was at milepost 400 and the analyses
in Sections 3.3.2.2 through 3.3.2.4 suggested a break near milepost 500. Since
the Gulf coast turned most sharply around milepost 450, we decided to select this
point to delineate our first homogeneous region. We had initially divided the
south-facing portion of the Gulf coast (mileposts 400-1100) into two portions,
with the break near the Mississippi delta (milepost 700). We did this to
consider the possibility that storms affecting the eastern and western portions
might be different. The results of the statistical analysis did not support this
division. The statistical analysis suggested extending this region to the middle
portion of the west coast of Florida. However, the storms affecting the west
coast of Florida tend to be weaker (see fig. 8). Since the frequency of
landf ailing storms on the west coast of Florida is low, we felt that the
statistical techniques were not able to discriminate this difference. We
selected milepost 1050 as the dividing point between the two regions. Again, the
coastal orientation changes most rapidly near this point.
3.3.3.2 Florida Coast. The Gulf and Atlantic coasts of the United States were
considered separately because of their differences in geographical and
meteorological conditions. Division of the Florida peninsula involves
consideration of a number of factors, some of which suggest contradictory
groupings. The statistical analyses as well as meteorological considerations
(e.g., Kuo 1959) demonstrate that hurricane characteristics vary noticeably with
latitude. This is due to both latitudinal variations in atmospheric circulation
patterns and generally decreasing sea-surface temperature with increasing
latitude. Warm water has been identified as an important factor in supporting
the energy transformations necessary to maintain a hurricane circulation. These
facts suggest that the data for all of Florida be considered homogeneous. In
fact, the results of the cluster analysis support such a grouping for the
southern portion of the peninsula. However, coastal orientation suggests
dividing the data sample near the southern tip of Florida. Tropical circulation
typically is associated with easterly flow. Therefore, storms moving from the
east would strike the east coast of Florida. The synoptic scale meteorological
patterns under such flows are most conducive to development and maintenance of
hurricanes. On this basis, we suggest that there is the potential for strong
hurricanes to affect the east coast of Florida.
For a hurricane to strike the west coast of Florida, it must have a westerly
component in the direction from which it approaches the coast. Usually such
motion is associated with storms that have undergone recurvature. Recurvature,
as opposed to more random variations in storm direction, is almost always
associated with the tropical cyclone becoming embedded in the westerlies. This
is usually a critical transition in the hurricane's lifecycle. When this
happens, the upper-level outflow necessary to maintain the warm-core circulation
is impeded. Such storms tend to weaken and some take on extratropical
characteristics. Occasionally, hurricanes that formed in the Gulf of Mexico
moved across the Florida peninsula in a west to east direction before recurving
northeastward. Though intense hurricanes were reported to have struck near Cedar
Key and Tampa Bay in the mid-1800' s (Ludlum 1963), it is reasonable to expect
that, on the average, hurricanes striking the west coast of Florida will probably
be weaker. The data (since 1900) in Figure 8 lends support to this observation.
42
3.3.3.3 Atlantic coast. When five clusters were used, the cluster analysis
suggested that the Atlantic coast include 3 regions: (1) the southern half of
Florida peninsula, including the west coast, (2 ) a segment from about Vero Beach
(milepost 1600) to the vicinity of Cape Hatteras (milepost 2250), and (3) a
region including all the coast north of Cape Hatteras. Our a priori judgment
suggested four segments, with only the boundary in the vicinity of Cape Hatteras
being common with the cluster analysis. The reasons for selecting milepost 1415
at the tip of Florida have been discussed in the previous section. As mentioned
in Section 3 .3 .2 .2 , the boundaries of a cluster represents a region, rather than
a clearly defined point. Examination of Figure 2 7 shows that from
mileposts 1600-1800 there is a broad minimum in frequency of landfalling
storms. In fact, it is probably reasonable to place the boundary between
clusters any place within this region. For this reason, we chose to maintain
milepost 1800 as the divider between the homogeneous cluster of storms striking
the east coast of Florida and those affecting the coast to the north. This point
is near the Florida-Georgia state line where the coastal orientation changes from
NNW-SSE to NE-SW.
Both our judgment and the statistical analysis support considering the region
from Florida-Georgia state line to the vicinity of Cape Hatteras as
homogeneous. Conditions to the north of Cape Hatteras may not be homogeneous,
either meteorologically or statistically. However, the region north of
milepost 2300 is specified as "homogeneous" because of the very limited number of
observations of landfalling storms in this area. In general, we did not base our
analysis for this portion of the coast on the results of formal statistical
techniques. We believed that the only way to treat this area was by exercising
meteorological judgment. Our analysis ensured consistency and a smooth
transition from the more data-rich areas to the south of this area.
3.4 Interrelations Between Hurricane Parameters
3.4.1 Brief Review of Previous Studies
Previous studies have suggested that some interrelations between hurricane
parameters may exist. TR 15 suggested specifically that:
1. hurricanes with P below 92 mb have small R;
2. for P q from 92 to 970 mb, there is "no detectable interrelation"
between P and R when the entire Atlantic coast was considered;
o
3. "if the latitudinal trend [along the Atlantic coast] is removed from P
and R, little local interrelation between P and R remains"; and
4. hurricanes that have recurved and move toward the north-northeast tend
to be faster (larger T) than those that are at the same latitude and
have a more westward component in the forward velocity.
National Academy of Sciences (1983) evaluated the FEMA storm-surge model and
indicated that:
1. The Tetra Tech report claimed no strong linear relations among any
hurricane parameters were found for the Gulf region as a whole;
43
Table 12. — Breakpoint values for contingency tables
Region: GLF A (0 <_ m < 4 50) GLF B (450 <_ m <1050)
Parameter Breakpoint Breakpoint
P Q 951 mb 965.5 mb
R 18 nmi 2 0.5 nmi
T 11 kn 13 kn
2. Earle indicated tbat there was no significant relation between
forward speed and central pressure depression over or near southwest
Florida (see p. Ill, National Academy of Sciences 1983). This implies
no significant relation between T and P because central
pressuredepression is defined as the difference between P Q and a
peripheral pressure that is usually near 1013 mb.
3. For the middle section of western Florida coast, R and 9 seem to be
dependent upon central pressure depression (implying dependence on
V-
Among suggestions listed above, Tetra Tech's claim was based on factor analysis
applied to all storm parameters. Others were based mostly upon qualitative
reasoning and no rigorous statistical tests were used to support the hypotheses.
3.4.2 Methods for Testing the Interrelations Between Hurricane Parameters
Two methods were used to examine the question of statistical independence:
contingency tables with a Chi-square test and the Spearman test. The contingency
table test is a categorical test while the Spearman test is a rank test. Both
methods are described in more detail in Appendix B.
3.4.2.1 Contingency Table with Chi-Square Test. Since the contingency table
analysis was designed for categorical data, the hurricane parameters had to be
separated into categories. Because the hurricane data are continuous, the choice
of boundaries between categories was somewhat arbitrary. The separation of the
data also had to meet the requirement that the expected count in each cell
could not be less than five in more than 2 percent of the cells in the
contingency table. Because of the limited sample sizes, we only used two-by-two
contingency tables. Only two segments had enough data to allow the Chi-square
test to be performed: the two western-most segments along the Gulf coast (GLF A
and GLF B). The breakpoints selected to create the categories are given in
Table 12. These breakpoint values divide the parameters into two groups - values
of the parameter less than the given value and those equal to or above the
breakpoint value.
3.4.2.2 Spearman Test. The Spearman test is based on interrelations between the
ranking (from one extreme to the other) of the observed values instead of on the
observed values themselves. This test does not require assumptions about the
distribution of the data; it is a non-parametric test. The Spearman test
statistic can be computed for a sample size as small as four (Conover 1971). It
can be used to test independence, positive correlation or negative correlation
between ranks of two random variables. The minimum sample size that is required
for reliable inference based on this test has not been established. Thus, the
test results obtained for small samples must be interpreted with caution. In the
44
Table 13. — Sample sizes of paired parameters of landf ailing hurricanes for
coastal segments
GLF A
GLF B
GLF C
ATL A
ATL B
ALT C
Milepost
Range
0-4 50
450-1050
1050-1415
1415-1800
1800-2300
2300-3 100
(P , R)
P , T)
(R, T)
23
28
13
17
16
6
24
29
13
17
16
7
23
28
13
17
16
6
discussion of test results, we also present the sample sizes to provide a
qualitative indication of the reliability of test results, i.e., the larger the
sample size the more reliable the result is likely to be.
3.4.3 Comparison of Results from Different Independence Tests
The comparison between results of the Spearman test and those of the
contingency table with a Chi-square test are shown in Figure 9. In each block,
the upper triangle shows the results of the Spearman test and the lower triangle
shows those of the contingency table with a Chi-square test. A symbol is given
for each intersection of a column of one parameter and a row of a different
parameter. The symbol I means that the pair of parameters are mutually
independent and the symbol * indicates that the sample size for the pair of
parameters was too small for the contingency table with a "Chi-square test.
The sample sizes of paired parameters of landf ailing hurricanes are listed in
Table 13. For coastal segment ATL C, there were only seven landf ailing
hurricanes recorded, and for one hurricane the R value was not available. The
sample size for ATL C was considered so small that no formal statistical testing
was done for this coastal segment. Only segments with sample sizes greater than
2 were sufficient to apply the Chi-square test.
Figure 9, indicates that each pair of parameters for the combinations of P , R
and T are mutually independent. For the pairs that have large enough sample
sizes, the results from the Spearman test and the Chi-square test agree with each
other.
3.5 Discussion
In general, the parameters P R and T for landfalling hurricanes are mutually
independent for the coastal segments throughout the milepost range 0-2300. For
mileposts greater than 2300 (north of Chesapeake Bay), the small sample size
prevents the determination of meaningful statistical results. The direction of
storm motion is limited by the coastal orientation and cannot be treated as a
random variable. For the purposes of storm-surge frequency computations, it is
our recommendation, based on the results of the statistical tests and on our
meteorological judgment, that all parameters be considered locally independent
for the entire Gulf and Atlantic coast, except for the special cases discussed in
Chapters 4 and 5.
The data available for tropical storms, and bypassing and exiting hurricanes
were inadequate to allow a statistical treatment. For landfalling tropical
storms, only forward direction and speed were available. For bypassing and
45
GLF A (0 < m < 450)
P o
R
T
P o
T
I
R
I
I
T
I
I
\
CHI-SQUARE
GLF B (
450 <
m <
1050)
p o
R
T
P o
\
I
I
R
I
I
T
I
I
\
ATL B (1800 < in < 2300)
P R T
P o \^ i i
R * \^ I
T * ■ * \
CHI-SQUARE
CHI-SQUARE
GLF C (1050 < m < 1415)
ATL A (1415 < m < 1800)
P o R T
P o \ Z 1
\
R * N. I
T * * \
P o
R
T
P o
I
I
R
*
\
I
T
*
*
\
IHI-SQUARE
CHI-SQUARE
Tigure 9. — Interralatioas between parameters of landf ailing hurricanes for the
Gulf and Atlantic coasts of the United States. Symbol m denotes milepost, I
means independent, and * means insufficient data.
exiting hurricanes, except for limited coastal segments, the sample sizes were
too small for meaningful statistical tests. In practical applications, these
classes of storms are treated as individual entities with separate frequency
counts and different probability distributions for corresponding parameters, if
warranted. The question of their interdependency was not resolved in this study,
but, based on the results for landfalling storms, we feel it is reasonable to
assume that these parameters can also be considered independent.
While consideration of the statistical analysis was integral to our
conclusions, our recommendations rely heavily on our meteorological judgment.
This situation arose because the data sample was characterized by large natural
variability. While the sampling period is on the order of a century, there are
generally fewer than 10-15 storms per year that reach an intensity sufficient to
be classified as tropical cyclones. In general, this amount of data is not
sufficient to counteract the natural variability of the sample, and to allow
standard statistical procedures to provide reliable guidance in answering the
question of whether the parameters are mutually independent.
We want to emphasize that our conclusion that the data can, in general, be
considered independent should be interpreted narrowly. We feel that, given the
data sample, there is no evidence to support quantifiable interrelations.
Because of the variation along the coast, both in the Gulf as discussed in
Section 3.3.2.1, and along the Atlantic coast due to the "latitude effect,"
independence should be considered to be applicable locally. This concept is
analogous to the idea of local homogeneity, discussed in Section 3.3.2.1. For
example, Figure 10 shows scatter diagrams of P , R, 9, and T as a function of
milepost for the Atlantic coast. There is a fairly clear tendency for all four
parameters to increase with the milepost value - this is the "latitude effect."
This correlation of all parameters with latitude could lead to the conclusion,
based on any number of statistical tests, that the parameters are interrelated.
However, this interrelation would not necessarily be between the parameters
themselves, but could be due to the latitude effect. For any limited area, even
if sufficient data were available, we feel that it is likely that the parameters
would be mutually independent. Because we present our results (chapts. 6-9) with
respect to milepost, the latitude effect, while being incorporated into the
analysis, has effectively been removed for the purposes of local storm-surge
computations.
Our recommendation that the parameters be treated as locally independent is not
meant to imply that we feel there are no interrelations between the
four parameters. Meteorologically, there are good reasons to suspect such
relations. What we are proposing is that the natural variability in the data
sample completely overwhelms any interrelations that may exist. The
recommendation is a practical one - there is no way, within the limits of this
study, to quantify interrelations between the parameters. Except for the special
cases discussed in Chapters 4 and 5, there is no justification for attempting to
specify, rather arbitrarily, possible interrelations. Further analysis of data
from areas beyond those considered in this study may be sufficient to determine
whether interrelations do exist, and to support quantification of such
relations. However, if such work were to be pursued, care should be taken to
assure that conclusions drawn from such a study were applicable to storm-surge
computations along the Gulf and Atlantic coasts.
47
»oo 139* i*oo iToo iao» noo iooo 210* 2200 2Jo« 2«as 23ot !tti 2Tot :«o. 2*1* sot* not Ugi
MILEPOST (ami)
(a) Central Pressure
no ISO! !*«• -700
2000 2100 2200 2300 2100 2300 2M0 2700
2900 300* 310* MOO
MILEPOST (nmi)
(b) Radius of maximum winds
Figure lO.-Landfalling hurricane parameters versus adlepost for the Atlantic
48
coast.
i»9< 1:39 itci 1T0* :ano i«o» 2oao 2109 2209 2399 2*09 23a* 2*
MILEPOST (nmi)
(c) Forward direction
2ioa loo* ;iai
1»10 1509 1*00 1730 1300 1909
U00 220* 230* 2»aO 2S09 2*00 2T09
MILEPOST (nmi)
(d) Forward speed
2191 3009 3109 3209
Figure 10. — (continued).
49
4. THE JOINT PROBABILITY QUESTION:
CENTRAL PRESSURE VERSUS RADIUS OF MAXIMUM WINDS
4.1 Introduction
An objective of this report "was to define climatological probability distribu-
tions of hurricane central pressure (P Q )> radius of maximum winds (R) , forward
speed (T), and direction of motion (9) along the Atlantic and Gulf coasts. In
calculating frequency distributions of hurricane-induced surges on the coast it
is necessary to combine the probabilities from the individual distributions. In
such applications, the question of statistical independence among the individual
probability distributions has to be addressed. For example, of all the hurri-
canes affecting a given coastal stretch over a long period of time, what fraction
of the storms are in both the upper 10 percent in intensity (P ) and size (R)?
If P and R are independent, the probabilities can be multiplied. In this case,
there would be a 1-percent chance of their joint occurrence. If P and R are
positively correlated, there would be more than a 1-percent chance of the simul-
taneous occurrence of a storm both this intense and this large. Similarly, if P
and R are negatively correlated, the joint probability is less than 1 percent.
Statistical tests may be inappropriately biased toward acceptance of indepen-
dence if the significance level chosen for the test is too low, especially
considering the high variability and relatively small sample sizes available for
this study. Dependencies which are meteorologically based may be present, but
may not lead to rejection of the null hypothesis of independence. Another point
that must be considered is whether or not certain interdependencies are expected
to extend across the entire spectrum of a given parameter or whether such
relations might be important only within some limited range of values.
4.2 Central Pressure Versus Radius of Maximum Winds
A significant joint probability question is whether hurricane size (R) and
intensity (P ) are independent. A storm that is both large and intense would
have enormous destructive power. Hurricanes with very large R's (in excess of
4 5 nmi) are generally found to be of moderate or weak intensity. In hurricanes
that have undergone recurvature and are moving northward in the Atlantic, often
becoming ext ratropical , the radius of maximum winds tends to become larger and
more ill-defined, and the central pressure rises. Extremely intense hurricanes
(low P ) and those with small radii of maximum winds tend to occur together
because, if angular momentum is conserved, a vortex contracts in size as it
increases its rotational speed.
If we examine the data for P and R for the Gulf coast (table 1), it is not
surprising that the calculated correlation coefficient was only 0.16. A
correlation coefficient this low indicates that the linear relation between P q
and R is not likely to be significant. However, a low correlation could occur if
a nonlinear relation existed between these two variables. It is also possible
that a relation between P Q and R could be masked by the high degree of natural
variability inherent in hurricane observations. If such a relation exists, it is
likely to be most prominent for intense storms where the dynamics that couple the
variation of both P and R are stongest and less susceptible to the masking
dependence of P and R, we choose to employ non-parametric statistics. A
non-
parametric test does not require specification of the form of the distribution,
50
Table 14. — An example of a general two— by— two contingency table
Condition 1 Condition 2 Total
Group 1 a b a + b
Group 2 c d c + d
Total a + c b + d n
thus, Che statistical test avoids the assumption of linearity. It can also
provide insight into behavior of the extreme portion of the distribution by
judicious selection of the P Q and R groupings. (See below.)
The test of interdependence of P Q and R involves comparing the two samples of
observations to see if the populations appear co be related. In other words, to
determine if a given P Q value is more likely to be associated with a limited
range of R values (interdependence), or whether any R from the complete spectrum
of values has the same probability as the distribution specified for R for every
? value (independence). We set up a contingency table, the form of the
tabulation is displayed conventionally in Table 14. The letters a, b, c, and d
3 re the count of occurrences in each group for a given condition.
We used Fisher's exact probability test (Conover 1971) to compare our
groupings. Fisher's test assumes that the marginal totals of Table 14 are fixed
(that is, the number of observations in each group and for each condition are
fixed), and tests whether the partitioning of frequencies (a, b, c, d) could have
arisen by chance. The probability of such an occurrence is calculated as,
a + c
( b ; d )
n
a + b
where ! "' '" j is a binominal coefficient ; — ; — - , hence
= (a + b)! (c + d)! (a + c)! (b + d)
P ~~ n! a! b! c! d!
51
Table 15. — Frequency of occurrence of different storm radii in two different
class intervals of hurricane intensity observed in the Gulf of Mexico, 1900-84
R < 15 nmi R > 15 nmi Total
P Q > 93 mb 16 47 63
P Q <_ 93 mb 3 3
Total 19 Ul 66
Table 15 sbows tbe number of occurrences of burricanes making landfall on the
Gulf coast, within different categories of central pressure and storm size. We
formed a null hypothesis, H Q , that there was no significant difference between R
associated with group 1 (P Q > 930 mb) and group 2 ( P Q < 93 mb). Fisher's test
gives a probability of occurrence by chance a value of 0.02. At the 5-percent
level we rejected H and concluded that there was a significant difference
between the two groups of hurricanes, in terms of occurrence of the specified
hurricane radius.
A similar test was applied to the parameters, P Q and R, for hurricanes
landfalling on the Atlantic coast. With a small sample size and a much larger
degree of scatter, the formal statistical test could not detect any significant
interdependence of these two parameters for Atlantic coast hurricanes. While it
is clear that a relation appears to be reasonable for the extremely intense
hurricanes, natural variability seems to overwhelm this effect for most of the
other (weaker) storms. Furthermore, it requires a much larger sample of data to
establish the functional form of the joint probability of two parameters with a
degree of reliability, as compared to specifying a single probabilitv
distribution.
The hurricanes listed in Tables 1 and 2 are insufficient to auantify anv joint
probabilitv relation that might exist over the full range of P and R. The data
must be supplemented by a measure of deduction and meteorological judgment.
Before reaching a conclusion, we supplemented our data base by including
extremelv intense hurricanes that occurred outside our main area of interest
(within 150 nmi of the Gulf and Atlantic coasts).
4.3 Meteorological Analysis
The basic observations used in our analysis of extremely intense hurricanes
(P<93 mb) were based primarily on wind and pressure data recorded by recon-
naissance aircraft. In some cases, central pressures were also obtained from a
search of other sources, including studies of individual hurricanes in the liter-
ature. Table 16 gives a list of hurricanes with P Q less than or equal to 93 mb
recorded during the period 1900-85, together with the radius of maximum winds
taken at the time of minimum central pressure. The R values for Hurricane Janet
of 1955 could not be determined because of a lack of wind data. Janet was a very
compact storm with winds reaching hurricane force only about 2 hr before the
arrival of the eye (Dunn et al. 1955). Estimated maximum winds of 2 00 mph were
reported just about 30 min prior to the passage of the eye over Swan Island. The
table also lists locations where the P and R data were observed. In all cases,
52
3 3 3 3
be
3
O
00
o
00
o
CO
in
co
v£>
O
2
00
2
CO
2
2
oo
2
O
2
en
2
O^
H
><
CNI
o>
00
in
CN)
CO
^O
(U
<U
M
J-l
3
3
«
CO
71
0)
01
CD
3 3
c c
CI
6
3
21
a
s
>
3
<3
a
O
o
o
o
o
CO
O
o
o
fa-i
CJ
2
2
a
2
2
2
2
M
c
3
•H
<
-a ^
co
s •
CO 2
CD
•U 73
CO 0)
s
„
,
1—1
>-,
CO
CU
£
N<
3
U
J3
<u
CJ
JC
c
CJ
o
u
<
<
o o
2 2
5 3
<r o r-
— < CO CN
CJ\ CTn 0>
O — i
\0 vD — H
CTi C^ O
r-» o
CTi 00
— i a>
a
a
a
a
CD
01
0)
0)
CO
CO
en
CO
,_|
4-J
CO
0)
•H
CO
,—1
CU
CO
T3
c
O
CU
C
JS
4-J
N
s
J-J
•H
cij
1-4
3
C
4J
■U
0)
3
s
M
•H
>
i— i
CO
co
o
cn
CO
3
0>
CO
CO
3
CO
, — 1
u
T)
a
W
S3
H
pa
CJ
U
<!
a
<c
53
the central pressure (P Q ) given in Table 16 is the lowest pressure observed in
the entire life span of each hurricane. The notation P Q used to designate the
central pressures in Tables 1 through 3 carries a different connotation. Tables
1 through 3 list the pressure that would generate a realistic surge on the open
coast in steady-state models currently used in flood insurance studies (relative
to the coast). In this chapter, P is used to signify the central pressure
values without reference to the time or place of observation (absolute minimum
V-
Figure 11 shows the locations of the 15 extreme hurricanes at the time of their
lowest central pressure. Out of the 15 extreme hurricanes, 6 occurred in the
Atlantic Ocean. The hurricane of 193 5 which struck the Florida Keys had the
lowest central pressure ever recorded in Atlantic hurricanes (892.5 mb). The
most intense hurricanes affecting the Gulf coast were Hurricanes Camille (1969)
and Allen (1980). A record low central pressure for the Gulf of Mexico (899 mb)
was reported in Hurricane Allen as it entered the Gulf of Mexico through the
Yucatan Channel.
Figures 12 and 13 show the tracks of these severe hurricanes together with
locations of reported lowest pressures at various times during the life span of
each hurricane. Central pressures of 905, 908, and 909 mb were observed in
Hurricane Camille (1969) near 2 5°N, 28°N, and at the time of landfall. There was
insufficient data to show detailed time variation of Camille's intensity between
the time she crossed 2 5°N and the coast. We assumed that Camille's central
pressure remained almost steady during this time period of about 3 6 hours.
Hurricane David (1979) reached its minimum pressure of 92 4 mb when the hurricane
was located some 100 nmi south-southeast of Puerto Rico. Its central pressure
rose above 93 mb and then dropped to 92 6 mb just before crossing the coast of
Hispaniola. Low pressures in Hurricane Allen (1980) were plotted at three
different locations because Allen went through three weakening/deepening cycles
in its life span. The occurrence of these three cycles in Allen strongly
suggests that geographical location is not a limiting factor in the occurrence of
extreme hurricanes.
4.4 Discussion of Analysis
Figure 14 shows a plot of P versus R for the hurricanes listed in Table 16.
Data from Hurricane Carla (1961) and a few data points from Allen (1980) (when P Q
was slightly higher than the minimum of 899 mb) were plotted in the same figure
to aid in determining the envelope of possible R values for extreme hurricane
conditions. An envelope was drawn through the highest R values for selected
intervals of central pressures. This curve indicates that observations of
extremely intense hurricanes with P less than 92 mb consistently have small R
values. The question of possible interdependence of P and R appears to be
clearest for the most intense hurricanes.
The second question which follows is whether the group of hurricanes included
in Figure 14 are representative of landfalling hurricanes. Of the six Atlantic
hurricanes, the 'Labor Day' hurricane (193 5) which had the lowest central
pressure ever recorded in the Atlantic, struck the Florida Keys. Hurricane
Camille reached its maximum intensity in the Gulf of Mexico; its central pressure
appears to have remained almost steady for the 36 hours before it crossed the
coast. Hurricanes David, Inez, Hattie, Carmen, Janet and Anita (see fig. 11)
54
«»
O
o
C g
a
Sjs^v
55
56
57
930
920-
910
900
89Q
• O
X
X •
/
ATLANTIC HURRICANE
CARIBBEAN " •
GULF " X
ALLEN &
5 10 15 20 25
RADIUS OF MAXIMUM WINDS (nmi)
30
Figure 14. — Plot of P versus R for extreme hurricanes listed in Table 16.
Additional data points from hurricanes Carla (1961) and Allen (1980) have been
included*
58
reached their maximum intensity prior to the time of landf ailing. The weakening
of Hurricane Allen (1980) prior to the time of landfall can he explained by the
presence of a warm high pressure ridge over the southern states. Similarly,
other cases of decreasing intensity prior to landfall could not be simply
explained due to the close proximity of the land mass. There is no reason to
believe that, under reasonable meteorological conditions, any of these hurricanes
could not have reached the coast while maintaining their maximum intensity.
4.5 Conclusions
There are insufficient data to specify a joint probability distribution of P
and R for extreme hurricanes on a regional basis. Intense hurricanes were
experienced on the Gulf coast, extending from the Florida Keys (1935 hurricane)
through the Mississippi coast (Camille 1969) to locations off the Texas coast
(Hurricanes Allen, Anita and Beulah). Small R's tended to be associated with
these hurricanes when their pressures were lowest. These facts suggest that
small R's are associated with intense hurricanes. There are seven observed R
values for hurricanes with central pressure less than 92 mb. These R values,
ranging from 6 nmi to 15 nmi, have both mean and ^median values of 10 nmi. It
appears that 10 nmi is a representative R value" for intense hurricanes. A
refinement can be accomplished by separating the intensity of the storms into two
different class intervals. We believe that an R value of 13 nmi assigned to the
class interval of 92 0-908 mb and an R value of 9 nmi assigned to storms with P
less than 908 mb would provide reasonable estimates consistent with observations
and accepted meteorological principles. We recommend the adoption of these
R values for the most intense hurricane categories.
5. OTHER JOINT PROBABILITY QUESTIONS
5.1 Introduction
Unlike P , R and T, 9 is restricted to ranges that depend on coastal
orientation, and, as discussed in Section 3.2.1.2, creates problems in treating
the direction data as a random sample. This chapter will attempt to examine
possible interrelations between P and 0, and between T and 9. While we will use
some formal statistical procedures, we want to emphasize that it is only for the
purpose of guiding our judgment about possible interrelations. Ho and
Tracey (1975) discussed in some detail possible relations between P and 6. It
appears that this interrelation is a localized problem for North Carolina, north
of Cape Hatteras. With the limited number of observations, it is not feasible to
specify the joint probability of the two parameters. To establish such a joint
probability relation requires a much larger sample size than that required for a
single probability distribution. An alternative approach in dealing with this
problem is to segregate the sample into subgroups.
*
It should be emphasized that the representative R value is a clima tologi cal mean
which excludes probable extreme values and may not be applicable in engineering
design and forecasting.
59
« 1 —
L
- — i —
— i—
- 1 —
— i 1 1 —
— i 1 1 —
1 1
i i i I
j-
A A -
r
A
A
r
A
i-
A A
L
A
A
*
*
*
*
A A
A
A
A
A A
A
A
A
A
A A
A
A
•
A
A A
A
A
A
i — i —
..i—
..;..
„i„
...l-
_-*..
...I..
..a~
— i a ;...
--A A A~
...A~
..A- i..
...A A A A™.
DIRECTION (deq. from north)
Figure 15. — Scatter diagram of direction versus speed of forward notion for
hurricanes landfalling on the Atlantic coast.
5.2 Forward Speed versus Direction of Storm Motion
In Che Atlantic, hurricanes tend to move north-northeastward to northeastward
after they recurve. These hurricanes generally move faster than westward moving
hurricanes at the same latitudes. Atlantic hurricanes that recurve near the
coast often strike either the North Carolina coast or the south shore of Long
Island or New England. Figure 15 shows a scatter diagram of direction versus
speed of forward motion for hurricanes landfalling on the Atlantic coast. This
figure reveals that a direction of about 180° appears to separate the speeds into
two groups. The group with high speeds (right hand side of fig. 15) is
associated with directions from 180-220°, while the slower speeds are associated
with the full range of directions. This suggests that landfalling hurricanes
moving north-northeastward tend to have higher speeds of translation than those
coming from a direction with an easterly component. It is of interest to note
that these fast-moving storms entered the coast north of 33.5°N. These
hurricanes crossed the coast either near Cape Hatteras, North Carolina or in the
Long Island-New England area. These are the only areas along the Atlantic coast
whose coastal orientation allows storms moving from this general direction to be
classified as landfalling hurricanes. Storms entering the coast south of Cape
Hatteras, North Carolina, are generally hurricanes of Atlantic origin that move
in a northerly direction after recurvature or those that exited the Florida and
Georgia coast. Storms landfalling on the south shore of Long Island or New
England are usually hurricanes that moved parallel to the coast of Maryland,
Delaware and New Jersey. They could be classified as alongshore storms for
coastal locations to the south of the point where they made landfall. There are
no landfalling hurricanes coming from the directions 180-220° south of 33.5°N
because of the way storms are classified: by definition, storms coming from those
directions (180-220°) are either exiting or alongshore storms.
60
Table 17. — Comparison of speeds of landf ailing and alongshore storms for the
vicinity of Charleston, South Carolina
Percent of storms 5 20 40 60 80 9T
Landf ailing storms (kn) 5.6 7.2 9.5 12.2 15.1 19.2
Alongshore storms (kn) 6.6 8.6 10.8 13.5 17.6 23.5
Difference TTo l74 K3 HI FT! 4~7T
As indicated in Chapter 3, 9 and T for landf ailing storms generally vary with
increasing latitudes. The correlation coefficient of T and landfalling latitude
on the Atlantic coast is 0.71, and 0.45 for 9 and latitude. An examination of
the scatter diagram for T versus latitude (see fig. lOd) reveals that hurricanes
with speeds greater than 20 kn struck the coast north of 33°N, and that all the
hurricanes which crossed the Long Island-New England coast were fast-moving
storms. Thus, hurricanes landfalling at the northern latitudes tend to move at
higher speeds than those making landfall to the south. Though there are
limitations in the data samples for 9 and T as previously indicated, it appears
that hurricanes landfalling on the northern Atlantic coast may be different from
those making landfall to the south. However, when we examined the data within
homogeneous regions (concept of local homogeneity, as discussed in sec. 3.3.2.1),
9 and T for landfalling hurricanes appeared to be independent. The apparent
relation is attributed to the latitude effect, as discussed in Section 3.5.
Figure 16 (from Myers 1975) shows cumulative probability curves of forward
speed for alongshore and landfalling storms for the Charleston, South Carolina
area. The plots suggest that alongshore storms move only slightly faster than
landfalling storms. Twenty percent of alongshore storms move at speeds faster
than 17.5 kn, while 20 percent of landfalling storms move at speeds faster than
15 kn. Differences for the other 80 percent of storms are typically just over
1 kn, as shown in Table 17. This difference is within the range of expected
error in measuring storm speeds and suggests no relation between T and 9.
5.3 Central Pressure versus Direction of Storm Motion
5.3.1 Gulf Coast
Hurricanes landfalling on the Gulf coast generally arrive at the Texas coast
from an easterly direction, or strike the Florida Panhandle, Alabama, Mississippi
and Louisiana coasts from a southerly direction or cross the west coast of
Florida from the south-southwest to the southwesterly directions, as shown in
Figure 17. It would be easy to assume that these track directions come from
different populations. The Mann-Whitney test, which can be used to evaluate the
homogeneity of two samples, indicates that there are significant differences
among track directions in the three different zones on the Gulf coast. However,
the solid line in Figure 17 is the variation of the perpendicular drawn to the
smoothed coastline of Figure 1. The close correspondence between the data and
this line is simply a result of the restriction in directions imposed by
classifying these storms as landfalling hurricanes. Tests of interdependence of
P and 9 using contingency tables and the Spearman rank tests for the three zones
61
■on
>^ — '
r
!
UkMOPAkUNO
HURMIOUMS
J /
a L
• •/
-
03
" /l
2
• / '
|
-
•--¥ ■»
-
i»
I /•
& «
•!/
_
Z
-J
o
/ ♦
x L
lil 1
•
a.
a i
£ <ot-
-
<
_i
=
i i-
r
■ */
--
.
u
a !
< !
»L
-
/'
,7
— l
Ca)
i
5
I
'0
s
aj :s
■ORWARD SPEED Ckn)
r CRWARD SPEED (kn)
Figure 16. — Probability distribution of forward speed of (a) landf ailing, and
(b) alongshore hurricanes in the vicinity of Charleston, South Carolina, for
the period 1386-1973 (from Myers 1975).
62
530 400 600 300 1000 1200 1400 1600
MILtPOST Cnmi)
Figure 17. — Plot of forward direction versus ailepost for the landf ailing
hurricanes on the Gulf coast of the United States. The solid line is the
perpendicular to Che coastal orientation as a function of siilepost value.
50
45--
2 40:-
a
- 35:-
o
t 30i
25 :
20- r
20
40
80 100 120 140 160
FORWARD DIRECTION (dag)
80
200 220
Figure 18. — Variation with latitude of direction of forward motion for hurricanes
landf ailing on the Atlantic coast.
63
Table 18. — Partition of P Q and 9 for landfalling hurricanes striking the Atlantic
coast south of 33.5°N
P o i. 945 mb p > 945 mb Total
9 >_ 95° 3 15 18
9 < 95° 4 4
Total 3 19 22
separately show no evidence of interrelations between the parameters. However,
this conclusion must be interpreted narrowly: independence is with respect to
landfalling storms. Because of the variation of the coastline, this should also
be considered locally independent, in the same sense as described in
Section 3.5. It should not be extended to the underlying populations that
contain the full range of possible values without more detailed and extensive
analysis.
5.3.2 Atlantic Coast
On the Atlantic coast, the interrelations of P Q and 9 are masked by their
correlations with latitude. Figure 18 shows the variation with latitude of the
direction of motion for hurricanes landfalling on the Atlantic coast. The plot
suggests two groups of storm track directions. These two groups appear to be
separated by a forward direction of about 170° (vertical line on fig. 18). From
a meteorological standpoint, the data sample suggests the existence of two
distinct groups: (1) landfalling hurricanes crossing the Atlantic coast from
easterly directions (20-170°), which are westward moving hurricanes embedded in
the basic easterly current, and (2) landfalling hurricanes coming from 170-220°,
which are hurricanes moving northeastward after recurvature. There is also a
stretch of the coast, from 33.5-3 7°N, which apparently includes hurricanes from
both groups (dashed horizontal lines in fig. 18).
Statistical tests of homogeneity, using contingency tables and the Mann-Whitney
test, indicate that storm track data north of 37°N are significantly different
from similar data Co the south. These results also suggest that there are two
distinct groups of storm-track directions for landfalling hurricanes along the
Atlantic coast. Since the data along the entire Atlantic coast cannot be
considered homogeneous, it is inappropriate to consider the interdependence of P
and 9 for these data without separating the sample into separate groups.
5.3.2.1 Atlantic Coast, South of 33.5°N. We considered the data sample of
landfalling hurricanes for the Atlantic coast, south of 33.5°N, in the form of a
2X2 contingency table. We estimated the probability that specific
partitionings of the frequencies arose by chance. One partition of the data can
be made as shown in Table 18. This contingency table shows the number of
occurrences (frequencies) of hurricanes within different categories of P Q and
9. We then formed a null hypothesis that the noted distribution of observations
(frequencies) arose by chance, that is, there was no significant difference
between 9 _> 95° and 9 < 95°. The Fisher exact probability test gives a 0.53
probability of occurrence by chance. This indicates that we cannot reject the
null hypothesis at the 5-percent level. We further tested for different
groupings by changing the dividing line for both track directions and central
pressures. These tests also yielded results which did not allow us to reject the
64
145 £30 215 200 185 170 155 140
DIRECTION (deg)
10 95
Figure 19. — Histogram for direction of storm motion for the 2.5'
longitude block centered about Key West, Florida.
latitude and
null hypothesis. We concluded that, at the 5-percent level, there is no
significant difference between the two groups of hurricanes, in terras of
occurrence of the specified direction of storm motion. In other words, there is
no detectable relation between P and 9.
o
This conclusion is based on the total data sample. However, there may be
localized areas that could exhibit characteristics different from this general
conclusion. The data sample is inadequate to detect such situations. For
instance, an interrelation between P and might occur locally near the southern
tip of the Florida peninsula and the Florida Keys. Figure 19 shows a histogram
for direction of storm motion for a 2.5 degrees latitude and longitude block
centered about Key West. This histogram indicates a bimodal distribution for
direction of storm motion with storms traversing the 2.5 degree block both from
the southeast and the southwest. It is generally observed that storms coming
from an easterly direction are more intense than those coming from a westerly
direction. These localized interrelations between P , 9, and possibly between
other parameters need further scrutiny. It is left to the user of this report to
look at conditions at specific locations more closely. The treatment of storms
affecting the Cape Hatteras area that follows in Section 5.4 may be used as a
guide.
65
5.3.2.2 North Atlantic Coast. Examination of Figure 10a showing the latitudinal
variation of pressure suggests no noticeable variation with milepost for the
northern Atlantic coast. Meteorological conditions associated with the increase
in central pressure with increasing latitude are discussed in Chapter 7. This
feature is not obvious from Figure 10a. Consideration of Figure 10c for storm
direction shows a variation due in part to variations in coastal orientation, but
primarily due to synoptic-scale meteorological conditions. A large scale high
pressure system (the Azores-Bermuda high) usually is centered off the coast
creating a clockwise flow around it during the hurricane season. In association
with this high pressure system, storm direction tends to turn clockwise as the
storms move northward. This is the main explanation for the variation shown in
Figure 10c. In the absence of adequate data to test for interrelations
independent of latitude, it is our judgment that the concept of local
independence is appropriate for the northern part of the Atlantic coast.
5.4 Cape Hatteras Area
There are a number of coastal locations that, because of geographical features,
are probably not well represented by the generalized results presented in this
report. Such areas include protrusions, such as the Mississippi delta, the
southern part of Florida, Cape Hatteras and Cape Cod. It also includes major
bays and partially enclosed bodies of water, such as Chesapeake Bay, Delaware Bay
and the New York Bight. The paucity of storms affecting any one of these areas
makes generalized analysis such as done in this report impossible. They must be
examined on an individual basis. To illustrate some factors that might be
considered in such an analysis, we studied the area around Cape Hatteras. What
follows includes consideration of the more important factors for this particular
location. Some aspects of the approach might not be equally appropriate for
other locations.
One reason for selecting Cape Hatteras was based on consideration of
Figure 18. It appears that between 33.5 to 37.0°N, the storms may include
different types of hurricanes. For the coastal region from Cape Hatteras, North
Carolina to Virginia Beach, Virginia on the Atlantic coast, hurricanes
landfalling from the southeast quadrant cover the full range of intensities from
severe to weak. Occasionally, a hurricane meanders and strikes this stretch of
the coast from the northeast quadrant; observations indicate that these storms
have been weaker than those coming from the southeast. They have been weakened
either by unfavorable conditions in the troposphere or by the reduction of energy
supply while drifting over cold water. These storms, which typically move at
less than 15 kn, generally have slower speeds of translation than storms entering
the coast from the southeast quadrant. Therefore, a separation of P and T, as
well as P and Q, between landfalling storms from the southeast and northeast
quadrant was considered. The data for all landfalling hurricanes do not suggest
that R differs much depending on 9. Therefore, the R probability distribution as
given in Chapter 8 is recommended for both storm categories. Portions of the
statistical treatments used below were formulated by Ho and Tracey (1975).
5.4.1 Parameters for Landfalling Hurricanes from Northeast Quadrant
A special analysis was made of tropical cyclones landfalling from the northeast
quadrant. Hurricane Doria (1967), which was a tropical storm at landfall, was
used from Table 2, and, to expand the sample, data from other tropical cyclones
66
(1886 to 1984) moving from a northeasterly direction within an area west of 70°W
and north of 32 °N were also used. Tracks for Doria and these seven additional
storms are shown in Figure 2 0. These eight central pressure values were used in
the estimation of the cumulative probability curve shown in Figure 2 1
(curve A). The speeds of forward motion for the same storms were measured from
storm track maps (Neumann et al« 1981), and were used to help establish the
probability distribution shown in Figure 22 (curve A).
5.4.2 Parameters for Landf ailing Hurricanes from Southeast Quadrant
To obtain the probability distribution of central pressure for storms
landfalling from the southeast quadrant, the probabilities for northeast quadrant
tropical cyclones were subtracted from the overall probability for all
landfalling storms. The probability distribution thus obtained was also checked
against a direct sample of storm data. The resultant distribution for the
southeast storms (fig. 2 1, curve B) differs only slightly from that of all
landfalling storms. Speed of forward motion probabilities were evaluated in a
similar manner (fig. 22, curve B).
5.4.3 Landfalling Track Frequency
A discontinuity of track directions at Cape Hatteras can be seen between the
curves in Figures 44 and 45. The frequency of storms landfalling from the sector
91-160° is approximately the same immediately north and south of the Cape.
Landfalling storms from the other possible directions - 160-240° south of the
Cape and from the northeast quadrant north of the Cape - are not of equal
frequency. The overall frequency of landfalling storms (fig. 27), which was
averaged along the coast by using a smoothing function, was adjusted to define
this discontinuity. A track count of storms from the northeast quadrant and the
91-160° sector crossing overlapping two-degree latitude and longitude squares was
examined separately. The sum of these frequencies was checked against the
frequencies of all landfalling tropical cyclones. Figure 23 shows the resulting
frequencies with which hurricanes and tropical storms entered the coast from
different sections both north and south of the Cape. The plotted points show the
frequencies of all tropical cyclones at 50-nrai intervals (determined from
fig. 27).
6. FREQUENCY OF HURRICANE AND TROPICAL STORM OCCURRENCES
6.1 Classification of Hurricanes and Data
The frequency with which a coastal area has experienced tropical storms and
hurricanes during the period 1871-1984 is analyzed in this chapter. The data
have been divided into three categories of storms that affect the coast in dif-
ferent ways: 1) landfalling storms, 2) exiting storms, and 3) alongshore
storms. The frequency of storm occurrences is defined as the number of tracks of
each category of storms per year per nautical mile along a smoothed coast. The
term "smoothed coastline" is discussed further in Section 6.2.1.2 and a smoothed
coastline, defined objectively, is shown in Figure 24.
The statistics on the frequency of hurricane and tropical storm occurrences are
based on the yearly storm track charts by Neumann et al. (1981) from 1871-1980,
and from their annual updates between 1981-1984 (published in Monthly Weather
Review ). Following the criteria used in the track charts, tropical storms are
67
+
JUL. 1934
+
4-
OCT. JUL.
I 897 I 90 I
SEPT.
1889
/ SEPT.
1967
SEPT.
972
+
OCT.
913
NOV.
I 935
Figure 2 0. — Track of tropical storms and hurricanes showing motion from northeast
(from Ho and Tracey 1975).
68
RETURN PERIOD (yr)
.001 1. 1 I.I
-i i-t-
1.5 2 3 4 5
'l' I I I 'l ' I
25 50
1 ■ ■■ ' ■ i ■
100 500 1000
'I rnvl i 'r ■ I ■!■
NE LANDFALLING
(A),
"SE LANDFALLING, WRIGHT MONUMENT, N.C.
'(B)
920L-LL
. I .5 1.0 5 10 20 30 40 50 SO 70 80 30 95 96 97 98
CUMULATIVE PROBABILITY
I I I I I I l I I I l I
99 99.5 99.7 99.8 99.:
Figure 21.— Cumulative probability curve of central pressure for landf ailing
tropical cyclones adapted for Wright Monument, North Carolina.
RETURN PERIOO (yr)
3 4 5
'I ' I
2 5 50 100
t— I — i' " i : i ' i ' i ' i i ' ; n ' ! i
500 1 000
SE LANDFALLING STORMS
NE LANDFALLING STORMS
WRIGHT MONUMENT, N.C.
i i i i i i i i i i i i
• 1 .5 1.0 5 10 20 30 40 50 60 70 30 90 95 96 97 38 99 99.3 99.7 99.8 99.9
CUMULATIVE PROBABILITY
Figure 22.— Cumulative probability curve of speed of storm notion adapted for
Wright Monument, North Carolina.
69
1 1 1 1 1 1
Hovia i
VINOHIA
1 i
1
1
i -
9 -
-
■eA-'O'N
-
1N3WPNOW
1H9IHAA
-
OA1VS
O
/ °
/ *
e -
c
X
UJ —
Q
cc
NOAV
d ~~
- 2 —
5 _
o
X
li.
UJ _
U
2
<
40 —
3dVO
131NI
J
sxoovaoo
o
1 >
-1
-
i
'
!
i
i
inoxocn
— 3dVO •
L
.L _
-
1 I 1 ! 1 1, .1
. 1
! !
i
, !
Ciujuoi/JAQoi/SWaOlS) A0N3nO3Hd waois ONmvdQNxn
70
Figure 24. — Smoothed coastline obtained by applying the objective smoothing
function.
71
defined as storms with maximum winds 34 to 63 kn, and hurricanes as storms with
winds 64 kn or greater. The track charts also show extratropical stages of the
cyclone tracks when the tropical circulation was modified as the cyclone moved
into a nontropical environment. Beginning in 1972, the term subtropical was
adopted as official terminology to describe such storms. Satellite imagery and
other observational evidence enabled Hebert and Poteat (1975) to reexamine the
official Atlantic hurricane tracks and to identify subtropical portions of the
cyclone tracks since 1968. We included, in our frequency counts, subtropical
storms and extratropical storms which have intensity equal to or greater than
that of a tropical storm. For conciseness we use the term "tropical cyclone" in
this report to include all four classifications. Storms classified as "tropical
depressions" and "subtropical depressions" (maximum winds less than 34 kn) are
not included in the statistics.
6.2 Frequency of Landfalling Tropical Cyclones
Determination of the frequency of landfalling storms in a given area would be
relatively simple if a sufficiently large sample were available. However, data
are available for only 114 years, from 1871-1984. Inspection of this sample
reveals variations within short coastal strips which are likely to be chance
occurrences due to the relatively small sample size. A goal of this report was
to smooth out such variations, and to portray the characteristics of the
population , not the variability of the samples. Special effort was made to take
into account the effect of coastal orientation on the frequency of storms.
6.2.1 Direct-Count Method
The most direct method of assessing the frequency of landfalling tropical
cyclones is to count the number of storms striking the coast. The number of
entries was totaled for each 50-nmi segment along the smoothed coastline from a
point some 2 50 nmi south of the Texas-Mexico border to the Maine-Canada border
(see fig. 24). We created extensions of the Gulf and Atlantic coastlines at the
tip of Florida. We "extended" the Gulf coast from Cape Sable to the Keys,
stopping at its intersection with 81 °W longitude, as shown in Figure 2 5. We
"began" the Atlantic coastline at approximately 82.5°W, and continued it eastward
along the Florida Kevs to the mainland (see fig. 2 5). A storm could only be
counted once on each "coast." The extensions were used for estimation of the
probability distributions of storm frequency, P and R. We did not use the
coastal extensions for T and 9, since these data sets included both hurricanes
and tropical storms; we felt that the data were adequate to resolve the variation
of T and 6 along this part of the coast. The Gulf coast analysis stopped, and
the Atlantic coast analysis began at coastal reference point 1415.
For the period 1871-1984, 307 tropical cyclones entered the Gulf coast, and 193
entered the Atlantic coast, not including storms passing the Florida Keys west of
81 °W. The 50-nmi segment counts were smoothed by using the smoothing function
described in Section 6.2.1.1. Figure 2 6 shows the frequency plot of these
discrete storm entry values at 50-nmi intervals (points joined by a dashed line)
and the smoothing obtained as described in the next section. These frequencies
depict tracks of storm centers, but do not take into consideration the lateral
extent of coast affected by an individual hurricane. The damage swath from a
major hurricane can cover more than 100 nmi of coastline. The frequencies of
occurrences given in terms of storms per 100 yr per 10 nmi of the coast (vertical
scale in fig. 2 6) represent long-term averages of tropical cyclones which include
72
/
it Petersburg
SOUThf,
• Parish _ I "auchula 2 NW
'•II -TS-
w Mountain „.iie. I - L .aw I
Bartow .^ J
3absoa Park w -0- |
Oasia Fisnin* Lodge
X--!
-<> Avon Park -3-1 yr>ro
3radenton Exp 3ta w j | "V f" Fort Drum 3 NW
^V O- ■ ~ort Green 12 WSW Cte Soto City 4 SW
• O Q Comwell 4 X* j
l J Lake Placid 2 SW "^ j
Myakka-Sivr it Park'" > O^echobee 9 V |
> " — ■ it - CENTRAL '^ * '
Longboat Key_.
^-O- Sarasota
.enice
Arcadia '
Okeechobee Hrcn Gate
Venus 3 SE
I Port Mayaca S L Canal • I-f^A/FR
Moore Haven^L l' Canal ?olnt Gate 5 ^
-. . „ v >. I My Canal Point USDA»
! Ortona.2^^ J+ g^gy
-7-O-— Clewi s tonOtkJ iell ( , e w Glade HrC:l Gt - 4 ' ?aira 3eaci1
La 3elle r-, Ti^- iW Loxahatchee 1 _-0
1 ue Clewiston US En? ■ -&■ £jVf:
3elle Glade Exp Sta V" .„ „ , ^ ' '
J Felda. _Q. 1 j * ?ala 3eac!i WB AP
% -Q- \J^-?£/ ^ • Oevils Garden Tower • . <>■
,?t Myers #B AP I 1 I N Sew River Canal 1 Hypoluxo I
~\
O 1
Lake Trafford
.V Mew River Canal
Miles City Tower '.
*»pies EVERGLADES'-, Lauderdale Exp sta ^o"
j Pennsuco 4 SW -Soma ' ~f* ■_.
J
3oca Sat on 5 *
;— '-' I
PomDano Beach
9" I
Ft. Lauderdale 3ahia-Mar
Fort Lauderdale -O-
Everglades
lani *B AP
ami Canil
Hialeah , _ ■ _ 1
Miami WB City
ami 3each
„"9~ ykxsm-L 3ay Fror
Miami 3 * CT^ndall 2 £
ANq j
Tamiami T 40 Mi 3d -<^-
Coconut Grove 7 5 -O-
30 AST C$ASt I
Exp ST:a«f
83 32
Figure 2 5. — Map showing expansions of west coast of Florida and the Atlantic
coast through the Florida Keys. Numerals are ndlepost between 1395 and 1500
(see fig. 1).
73
— EA3TPCRT. ME.
■•-BOSTON. MASS.
— NEW YCRK, N.Y
;ape HATTERAS. N.C.
— CHARLESTON, S.C
OAYTCNA 3EACH, FLA.
— MiAMI, FLA.
FT. MYERS. FLA.
— 3T. MARKS, r LA
•°ENSACCLA, -LA
— 3IL0XI, MISS. 0=T
LAKE CHARLES, LA
■GALVESTON, TEX.
•PORT ISABEL. TEX
o
t- a
isvoo do iujuoj./sav3A ooi./s3iaiN3 do aaswrm
D W ?0
U CB 4-t
3 o -a
74
storms ranging in intensity from weak tropical storms to intense hurricanes. In
a probabilistic sense, one storm per 100 years should be interpreted as that
event which has a 1-percent chance of occurrence per year over a 10-nmi coastal
segment.
6.2. 1.1. Objective Smoothing Procedure. The 50-nmi segment counts were smoothed
by weighted averaging over 11 data points. We used a weight function in the same
manner as in low-pass filtering in time series analysis. The adopted function
has the following assigned weights (after Craddock 1969):
W n = 0.300, 0.252, 0.140, 0.028, -0.040, -0.030; for
n = 0, ±1, ±2 , ±3, ±4, ±5, respectively.
An alternative smoothing procedure sometimes applied in climatological analyses
uses a running-mean [W = 1/(2N+1)]. The results thus obtained may have
distortions in phase angle variation (shifting of maximum or minimum
positions). The weighting function adopted here is designed to maintain the
average frequencies and phase angles of the original input series. These weights
were applied to all successive discrete values from south of Texas to the
southern portion of Florida, and from Key West to Maine. The end of the input
series was extended as a mirror image of the original series. Thus, smoothed
frequency estimates of landf ailing tropical cyclones for each 50-nmi interval
were obtained along the smoothed coastline, from Texas all the way to the
Canadian border. The two series were then connected to give a continuous
smoothed curve of frequency of landfalling tropical cyclones (solid curve of
fig. 2 6). Figure 27 shows the final frequency curve including an extension at
the southern tip of Florida depicting the frequencies for the Florida Keys (upper
portion of the curve).
6.2.1.2 Evaluation of Procedure. The direct count method derives its data from
a count of tropical cyclones at the coast and not out over the water. It gives
the best estimate of the variation along a smooth coastline of the frequency of
landfalling storms. However, it tends to obscure variations due to coastal
shape. A stretch of the coast that turns sharply in a direction almost parallel
to that of the predominant storm motion is less exposed than adjacent coastal
segments more nearly normal to the track direction. We have implicitly smoothed
sampling variability associated with small scale variations of the coast.
To identify areas where the implied smooth coastal direction differs
significantly from the actual coastline, a smoothed coastline was constructed.
Coastal locations at 50-nmi intervals along the Gulf coast and Atlantic coast
were smoothed using the smoothing function described in Section 6.2.1.1. These
points were plotted and a continuous line joining these points was drawn for both
the Gulf and Atlantic coastlines (fig. 24). This diagram reveals that this
smooth line cuts across the actual coastline at several places — most
significantly, across the Mississippi Delta, along the west coast of Florida and
across Cape Cod. For the most part, the smoothed coastline approximates quite
well the orientation of the actual coast.
Areas where a smoothed coastal direction differs substantially from the actual
direction may be detected in Figure 24. These areas may either be sheltered from
or exposed to the prevailing direction of storm motion more than the smoothed
coastal direction would suggest. Differences between these coastal directions on
75
— EASTPCRT. ME. ' ' i i
1 r— -7-i
~
V —
-
x. -
^80ST0N, MASS.
J-
-
^^^^ -
~NEW YORK. N.Y.
^ -
"
^■•^^
—
^s-
-
^^^■^ -
»CAPE HATTERAS. N.C.
^*^~~*~~~ -
.
r
— CHARLESTON, S.C.
S, -
-
\
—
x^^ -
^•OAYTONA 3EACH, FLA.
^N
—
^^s -
S- MIAMI, FLA. ^^^^*
— ■"■*
— J{^
—
•-FT. MYERS, FLA. / ^*-«»^ >< ^
-
— ^
-
S** ^
-
— 3T. MARKS. FLA. (
—
V
_
— PENSACOLA, FLA. \
— 3IL0XI. MISS. \
—
\
-
— \
-
i- LAKE CHARLES. LA. J
-
•■GALVESTON, TEX. f
v^^
-
—
— PORT ISABEL. TEX.
1 J 1 1 1
U 1 1 J
01
O
111
<
et aa <t o to c* at v
«•> «\i oJ oi *■ *- d o"
isvoo jo iuiuoi./sav3A o<h/s3!u±n3 jo aaawnN
I —
76
Che Gulf coast may be large enough to cause significant differences in
frequencies of landfalling tropical cyclones obtained from the direct-count
method. The effect of the coastal orientation on the frequency count can be
illustrated by differences in frequencies between the north-south segment of the
southern portion of the west coast of Florida and the east-west segment of the
Florida Keys. Because of the coastal orientation, the west coast of Florida is
subject to landfalling storms from the southwesterly direction, while the Florida
Keys are at risk from both the southwesterly and southeasterly directions. The
coastal extensions discussed in Section 6.2.1 helped in analyzing the data near
the southern tip of Florida.
Other areas that required special attention are the Cape Hatteras area and the
Apalachee Bay area. The treatment of a discontinuity in the track count at Cape
Hatteras was discussed in Chapter 5 (sec. 5.3). Assessing the frequency with
which tropical cyclones struck the coast along the Gulf of Mexico was more
complicated than for the Atlantic coast because of the small angle between
prevailing track directions and the coast, on the one hand, and varying coastal
directions on the other hand. In order to treat these problems in the Gulf, we
also made use of the track-density method in which storm paths are considered
independent of coastal orientation. For a detailed discussion of this approach,
see the Appendix in TR 15.
6.2.2 Discussion of Results
Figure 27 reveals that the range of occurrence of landfalling tropical cyclones
over a 100-yr period varies from a minimum of 0.1 storms per 10 nmi of smoothed
coastline near Boston, Massachusetts, to a maximum of 2.2 in the middle of the
Gulf coast of northwest Florida and the Florida Keys. A frequency of close to
2.0 storms per 10 nmi per 100 years appears to the south of Galveston, Texas.
Highest frequency of landfalling tropical cyclones on the east coast is in
southern Florida, and a comparatively high frequency appears to the south of Cape
Hatteras, North Carolina. The frequency of entries drops off rapidly from Miami
to Daytona Beach, Florida and from Cape Hatteras northward to Maine, except
around Long Island.
6.2.2.1 Areas of High Entry Frequencies.
6.2.2.1 (a) Northwest Florida. The high frequency of storm entries along the
northwest Florida coast near St. Marks suggests that this stretch of the coast is
a favorable crossroad for tropical cyclones that pass east of the Yucatan
Peninsula and those that recurve in the Gulf of Mexico. This coastal region is
also vulnerable to Atlantic storms that cross the Florida Peninsula.
6.2.2.1 (b) South Florida. A maximum in landfalling storm frequency appears
near the tip of the Florida peninsula and along the Florida Keys. The
southernmost portion of this area is exposed to both Atlantic and Caribbean
hurricanes. Generally, tropical cyclones strike the east coast of south Florida
from an east-southeasterly direction - a predominant direction for Atlantic
hurricanes before recurvature. The west coast of south Florida is vulnerable to
tropical cyclones moving in a northeastward direction after recurvature. The most
frequent areas of recurvature in the month of October have been near the Bahamas
and in the northwestern Caribbean (Cry 1965).
77
6.2.2.1 (c) Upper Texas Coast. The comparatively high frequency along the upper
Texas coast is partially caused by the predominantly westward-moving storms in
Che Gulf of Mexico during the early hurricane season. Only six storms have
recurved and moved northeastward (away from the southern Texas coast) during the
months of June, July, and August since 1901. These early season storms accounted
for more than half the total number of storms that struck the Texas coast.
6.2.2.1 (d) Cape Hatteras. The high frequency of storm entries just south of
Cape Hatteras, North Carolina (1.6 storms per 10 nmi per 100 years), is the
combined result of the number of northeastward moving storms that reentered the
North Carolina coast after exiting the east coast of Florida and Georgia in
addition to hurricanes of Atlantic origin that moved in a northerly direction
after recurvature. Almost 90 percent of the storms entered the North Carolina
coast, south of Cape Hatteras, in a northwesterly to a northeasterly direction.
6.2.2.2 Areas of Low Entry Frequencies. The frequency of storm entries is less
than 1 per 10 nmi of coastline per 100 years over the northern section of the
east coast from a point some 50 nmi north of Cape Hatteras northward to the
Canadian border and also in the vicinity of Daytona Beach, Florida. The
significantly lower frequency of entries north of Cape Hatteras, North Carolina,
is easily understandable. With a few exceptions, hurricanes recurving south of
Cape Hatteras either enter the North Carolina coast or move northeastward away
from the United States mainland.
6.2.2.2 (a) East Coast. Colon (1953) has shown the locus of points of highest
frequency of recurvature for different months of the hurricane season.
Hurricanes off the east coast of the United States frequently recurve between
latitudes 2 7° and 2 9°N during the months of July and September. For the other
months of the hurricane season, recurvatures occur at latitudes farther south,
following the shift of the subtropical ridge (Alaka 1968). The northern limit of
hurricane recurvature at about 2 9°N appears to coincide with an area of minimum
frequency of landfalling hurricanes along the east coast. Hurricane Dora of
September 1964 was the only hurricane that struck the northeastern Florida coast
in recent years.
6.2 .2 .2 (b) Gulf Coast. The relative minimum in storm entry frequency along the
west coast of Florida (compared to the mid-Gulf coast and the southern tip of the
Florida peninsula) can be explained by the prevailing westward motion of
hurricanes of Atlantic origin. The relatively low frequency of storm entries
(before 1985) along the Louisiana coast west of the Mississippi Delta is most
likely due to sampling variability. The inclusion of storm data for the 1985 and
1986 hurricane seasons which were not included in this study would have increased
the entry frequency for this area.
6.3 Frequency of Exiting Tropical Cyclones
6.3.1 Analysis
The freauency of exiting tropical cyclones was defined by a subjective smooth-
ing of 50-nmi segment coastal crossings. These counts were obtained from the
storm track information previously cited. A total of 152 tropical cyclones exited
the Atlantic coast and 20 from the Gulf coast during the period 1871-1984. The
shape of the coast, relative to storm tracks, and meteorological considerations
were taken into account in the smoothing. For storms exiting the coasts of
78
Florida, consistency in frequency and direction of movement was maintained with
the frequency of landfalling storms on the opposite coast. The objective
smoothing technique was not used in this analysis because the observed data are
closely related to the geographical features of the coasts and because of
physical considerations (such as direction of storm motion). For these reasons,
the smoothing of sampling variations of exiting storms that concentrated in these
areas of the Atlantic coast was done subjectively, taking into account
meteorological factors.
6.3.2 Results and Discussion
Figure 2 8 shows the smoothed frequency distribution of exiting tropical
cyclones. This curve indicates high frequencies along the coasts of northern
Florida and Georgia and along the North Carolina coast north of Cape Hatteras.
6.3.2.1 Gulf Coast. The comparatively few exiting storms along the northern
portion of the west coast of Florida agrees with the decrease of landfalling
storms northward along the Atlantic coast of Florida. A local maximum of exiting
storm frequency occurred near Fort Myers, Florida.
6.3.2.2 Atlantic Coast. The maximum frequency of exiting storm occurrence ap-
pears near Jacksonville, Florida, near milepost 1800, with 3 storms per 100 yr
per 10 nmi of the smoothed coastline (see fig. 28). The frequencies
decrease southward with 2.2 storms/100 yr/10 nmi near Daytona Beach,
1 storm/100 yr/10 nmi near West Palm Beach, and 0.3 storms/100 yr/10 nmi near
Miami, Florida. The frequency diminishes rapidly north of Jacksonville. Higher
values appear between Cape Hatteras, North Carolina, and Cape Henry, Virginia.
Many exiting storms along the Atlantic coast originally were eastward-moving
storms in the Gulf of Mexico. They can also be traced to storms that recurved
over the Gulf or over the Florida peninsula south of the 29th parallel and moved
northeastward north of the subtropical ridge. This last group accounts for the
high frequency of exiting storms over the northeastern portion of the Florida
peninsula. The concentration of exiting storms just north of Cape Hatteras and
Cape Cod reflects the orientation of the coastline and the comparatively high
counts of entering storms south of these capes.
6.3.2.3 Application in Tide-Frequency Analysis. The treatment of exiting storms
in tide-frequency analysis for the area north of Cape Hatteras was considered by
Ho and Tracey (1975). They noted that grouping the parameters into fewer class
intervals was sufficient for storm-tide computations because exiting storms pro-
duced lower tides. They concluded that exiting storms made little contribution
to the overall storm-tide frequencies. Figure 2 9 (from Ho and Tracey) is a graph
of tide frequencies at Wright Monument, North Carolina, for several classes of
storms. Curve 'd f shows the computed frequencies of exiting storms contributing
little to the total tide frequencies. Such minimal contributions from exiting
storms can be attributed to lower intensities associated with them and from
dynamic ocean conditions associated with exiting storms. All things being equal,
exiting storms give smaller surges than landfalling storms. Speed of storm
motion works inversely for surge generation between exiting/landfall storm.
Sensitivity tests should be conducted to determine whether omission of the con-
tribution of exiting storms could affect the desired level of accuracy of the
overall storm-surge frequencies. Exiting storms on the Florida coasts should be
considered because of their generally higher frequency of occurrence and stronger
79
— "EASTPORT, ME.
— 30ST0N, MASS.
-—NEW YORK, N.Y.
.CAPE HATTERAS, N.C.
— CHARLESTON, S.C.
OAYTCNA 3EACH, FLA
— MIAMI, "LA.
MYERS, FLA.
— ST. MARKS. FLA.
'PENSACOLA, FLA.
• 3IL0XI, MISS.
LAKE CHARLES, LA.
•GALVESTON, TEX.
•PORT ISABEL. TEX.
CN
isvoo do iujuoi./sav3A ooi./s3!aiN3 do aaswriN
30
16i — i t i r i r— 1 — r » i i | i
14
12
£ 10
O
UJ
X
UJ
Q
1 1 i i — r i i r
WRIGHT MONUMUMENT
10
SO
100
500
RETURN PERIOD (yr)
Figure 29. — Tide frequencies at Wright Monument,' North Carolina, for several
classes of storms: (a) landf ailing, (b) alongshore, (c) inland, and
(d) exiting hurricanes and tropical storms; (e) winter storms; (f) all storms
(from Ho and Tracey 1975>.
intensities due to limited overland reduction as they move across the relatively
narrow Florida peninsula.' For estimating exiting storm intensities, the reader is
referred to Chapter 10 for consideration of overland tilling; rates and Chapter 11
for application procedures.
6.4 Frequency of Alongshore Tropical Cyclones
6.4.1 Analysis
The frequency estimates for tropical cyclones that bypassed the coast were
based on the same maps and data period used above. A count was made of storms
intersecting 5-nmi intervals along lines drawn perpendicular to a smoothed
coastline centered at each of the coastal locations (A to Z) in Figure 30. The
same storm may have been counted several times as it moved parallel to the
coast. The cumulative track counts along each of the 2 6 lines normal to the
coast were plotted against the distance from the coast. A smooth curve was then
fit to the data on each of these freauencv Dlots.
Figure 30. — Accumulative count of hurricane and tropical storm tracks passing tbe
coast at sea (1871-1984). Based on counts along heavy dashed lines shown
projected normal to coast.
32
The frequency distributions were smoothed subjectively both along the coast and
perpendicularly outward. These results are shown on Figure 30 by isolines of
accumulated number of storm tracks bypassing the coast at sea for the
period 1871-1984. We then read from the map accumulated track counts at discrete
distances of 10, 20, 30, 50, 75 and 100 nmi from the coast and plotted them as
alongshore profiles. Additional track counts and frequency plots were made at
close intervals near areas where the alongshore profiles fluctuated greatly
because of either a geographic protrusion or a concave coastline. Analysis was
then undertaken to obtain a set of smooth frequency curves for the Atlantic and
Gulf coasts. The resultant curves are shown in Figures 31 and 32 depicting the
accumulated storm track counts in storms per 100 years at selected distances off
the Gulf and Atlantic coasts, respectively.
6.4.2 Results and Discussion
Figure 30 reveals that the maximum concentration of alongshore storms occurred
off Cape Hatteras, North Carolina. Fewer than five tropical cyclones bypassed
within 50 to 80 nmi off the coasts of northwest Florida, Alabama, and Mississippi
and within some 100 nmi of the Texas coast. The higher values off the
Mississippi Delta may be caused by geographic protrusion. There is a high
frequency of bypassing storms off the coast of Cape Hatteras for the same reason
that there is a high frequency of landfalling storms south of Cape Hatteras. The
gradient at a distance of 100-150 nmi off the Atlantic coast indicates that
storms frequently traverse at some greater distances off the coast rather than
bypassing near the coast. This may be explained by the existence of the
semi -permanent high pressure system (the Bermuda High) in the Atlantic and the
location of the Gulf Stream off the coast. Atlantic hurricanes approaching these
latitudes tend to recurve along the western edge of the high pressure cell. The
higher track counts between 100 to 150 nmi off the coast seem to be associated
with the mean position of the Gulf Stream. Because of the steep gradient of
bypassing storm frequencies at some distance off the coast, caution should be
used in determining a representative frequency over finite distance intervals
from the coast.
Figure 31 shows a higher number of storms bypassing the Mississippi Delta and
the southern tip of the Florida peninsula in the Gulf of Mexico. An analysis of
storm track counts passing through two and a half degree latitude and longitude
blocks in the Gulf yielded maximum concentration of storm tracks in an area
extending from south of the Mississippi Delta to western Cuba (diagram not
shown). This explains the high values shown in Figure 31. The minimum values
occurred off the Texas coast and the Apalachee Bay area because of the concave
coastline in those areas which minimized the count of bypassing storms near the
coast. Figure 32 shows similar peaks and troughs in the alongshore profile of
bypassing storm frequencies off the Atlantic coast. These extreme values also
appear to be associated with geographic features of the coastline.
7. CENTRAL PRESSURE
7.1 Introduction
Central pressure (P ) is a commonly used index of hurricane intensity.
Harris (1959) demonstrated that storm surge height is approximately proportional
to the central pressure deficit (AP = P - P ), other factors being constant.
This chapter develops probability distributions of central pressure for tropical
cyclones along the coast.
83
13SVSI IHOd
J 1 Li
O U5 -* CO CM t- 0) CO N (O Uf
^ m .....
(ja ocu/swaois ONissvdAa) siNnoo a3J.vinwnoov
84
o
o
o
CO
CM
T"
\
\
\
CM -
O u
* 5
C 3
i a
o o o
lO ^ CO
> O SO t CO CM i-
I 1-
(jx ooi/swaois ONissvdAa) siNnoo a3ivnnwnoov
85
is
I
a) "3
The data on which we developed the P Q probability distributions for the
Atlantic and Gulf coasts of the United States have been collected in Tables 1
through 3. Original sources of data are described in Section 2.2. Revisions
were made in P data from TR 15 where we verified suspect data not accepted in
previous reports and, in a very few cases, as an analysis judgment after
reviewing all the data. A description of the data analyses was included in
Section 2.3, and revised hurricane central pressures were listed in Table 4.
Tables 1 through 3 list parameters of all storms with a central pressure less
than 982 mb (29.00 in.) that crossed the Atlantic and Gulf coasts or passed
within 150 nmi on the seaward side of the coast. The criterion that central
pressure be less than 982 mb was based on the consideration that the computed
magnitude of cyclostrophic wind using this pressure value (as described in
sec. 2.3.1) is approximately the wind speed required for classification as a
hurricane . With central pressure available for an average of less than one
hurricane per year for the period of record for each coast (Gulf and Atlantic),
the data in Tables 1 through 3 form a limited sample.
7.2 Analysis
Cumulative probabilities of hurricane P were determined from tabulated values
listed in Tables 1 through 3 for overlapping zones, generally centered 50 nmi
apart along the coast (see fig. 1). The lateral extent of the zone over which
the data were pooled was 400 nmi along the Atlantic coast, and 500 nmi on the
Gulf coast. We used a shorter distance along the Atlantic coast because
latitudinal variations were more important than along the Gulf coast. The 50-nmi
criterion was modified in areas where the data were sparse.
On the Atlantic coast, between the mouth of Chesapeake Bay and eastern Long
Island, the overlapping 400-nmi zones were separated by 100 nmi, and a single
zone was used from Long Island to the Canadian border. Near the southern tip of
Florida, hurricanes that passed near Dry Tortugas, and those that crossed the
Florida Keys, together with Atlantic coast hurricanes were used to determine the
probability distributions of P at locations on the Florida Keys. The cumulative
probability curves, thus obtained, were used in the extension of the Atlantic
coast along the Florida Keys (see fig. 2 5).
In southern Florida, along the Gulf coast, the overlapping 500-nmi zones were
centered 100 nmi apart (instead of 50 nmi). Hurricanes that pass the Florida
Keys and make landfall in western Florida usually become weaker as they approach
the coast. Parameters for hurricanes passing the Florida Keys are listed in
Following the criteria used by NHC, hurricanes are defined as tropical storms
with winds 64 kn or greater. We realize that there have been storms with
hurricane-force winds and central pressures as high as 990 mb south of 3 5°N. The
982-mb criterion was used to put definite bounds on the data sample. In our
statistical analysis, cumulative probability curves for central pressure are
extended to cover the full range of hurricanes and tropical storms.
86
Table 1 and their characteristics near the time of landfall are given in
Table 3a. As discussed in Section 7.3.2.1, P Q values tend to be higher north of
Cape Sable. Treatment of the data near the southern tip of Florida was handled
differently because of the break at milepost 1415 (see sec. 6.2.1 and fig. 2 5).
In determining the cumulative probabilities for P Q at coastal reference points
1350 and 1400 (near Cape Sable), we used P values for 6 hurricanes observed near
Dry Tortugas instead of the weaker intensities measured near landfall points at
some distance north of the points of interest. This was done to minimize the
biasing influence of the large number of generally weaker storms to the north.
Tables 1 through 3 include only hurricanes with P below 982 mb. However, the
track count on which the storm frequency (chapt. 6) is based includes tropical
cyclones of both hurricane and tropical storm intensities. In the application of
hurricane climatology, frequency of a representative, clima tologically specified
hurricane of given characteristics is the product of the frequency of all storms
and the probability of a storm having those particular characteristics. In order
to ensure a higher leveJL of consistency in our analysis, we expanded the central
pressure probability distribution to include weaker hurricanes and tropical
storms, in the manner described below.
The first step in the analysis of central pressure data was to construct
cumulative probability curves for each 400- or 500-mile zone. The magnitude of
central pressure versus probability of occurrence was plotted. Determining the
probability to be assigned to a data point is commonly referred to as determining
the plotting position. A plotting position may be expressed as a percent from
0-100. Probability plotting of hydrologic or meteorologic data requires that
individual observations or data points be independent of each other and that the
sample data be representative of the population.
Gumbel (1958) proposed five criteria for plotting position relationships.
Several plotting relationships have been presented by Chow (1964). Benson (1962)
in a comparative study of several plotting position relationships found, on the
basis of theoretical sampling from extreme value and normal distributions, that
the Weibull relationship provided estimates that were consistent with
experience. The Weibull plotting position formula meets all five of the criteria
proposed by Gumbel. An evaluation of plotting position formulae is included in
Appendix C. All of the relationships give similar values near the center of the
distribution, but they vary in the tails. In TR 15, the Hazen plotting position
formula was used to assess the probabilities. One objection to the Hazen plotting
position is that the return period for the largest event is twice the record
length. In the present studv, the Weibull relationship was used in assessing the
probabilities of all parameters. This plotting position relationship can be
expressed as:
X 100
where p is the probability expressed as a percent of the total number of storms,
n, and m is the rank from lowest to highest. To get n for all tropical cyclones,
the count of central pressures (up to 982 mb) was adjusted similar to TR 15,
using the ratio of hurricanes to the total number of tropical cyclones based on a
direct count of storm tracks. The upper part of the curve for each graph is ex-
tended smoothly to 1003 mb at the 100-percent level to arbitrarily represent
CENTRAL PRESSURE Cm»>
Figure 33.--Cuaulative probability carve of central pressure of hurricanes
landfalling within (a) 250 ami of mi 1 epos t 250, near Corpus Christi, Texas, and
(b) 200 ami of milepost 1600, near Vero Beach, Florida-
tropical cyclones with central pressure greater than or eaual Co 982 mb.
Examples of cumulative frequency curves for two coastal zones are shown in
Figures 33a and 33b. The first is centered near Corpus Christi, Texas and Che
second near Vero 3each, Florida.
It should be noted chad the best fit cumulative probability curves were not
always the most consistent solution for successive 50-nmi increments. The
Question of how to deal with an outlier in an extreme value distribution analysis
is always debatable. The central pressure determined for engineering design
hurricanes (called standard project hurricanes) along the Atlantic and Gulf
coasts by Schwerdt et al. (1979) was used extensively as a guide in analyzing the
lower end of the cumulative probability curves for central pressure (see fig. 2.1
of Schwerdt 's report). In the example given in Figure 33b, central pressure data
which was used in plotting; the cumulative probabilitv curve for milepost 1600
near Vero Beach, Florida
included
value of 892 mb from the 193 5
hurricane,
Earlier studies (e.g., Schwerdt et al. 1979) indicated that a
hurricane with such a low P would have approached the intensity of a "probable
maximum hurricane" with a probability of occurrence as much as an order of
magnitude less than 0.1 percent. Undoubtedlv, this ? value would be considered
o
an outlier for the purposes of our analyses. In treating this outlier, more
weight was given to this storm in the analysis for the Florida Keys, where the
hurricane made landfall, than at Vero Beach, Florida. The decrease in intensity
of a "standard project hurricane" from the Florida Keys to Vero Beach was 3lso
used as a guide in the analvsis.
88
Using the smoothed set of cumulative probability curves of minimum central
pressure, we read off the 1-, 5-, 15-, 30-, 50-, 70, and 90-percentile points for
each increment and plotted then as alongshore profiles. Analysis was then under-
taken to obtain a set of curves representing a consistent view of the probability
distribution of P for the Atlantic and Gulf coasts. The resultant central
pressure values at selected percentiles for each increment were smoothed using
the same weighting function employed in Chapter 6 (see sec. 6.2.1.1).
The relative infreauency of hurricanes near the Canadian border and of P data
near the Mexican border forced us to subjectively adjust the results of the
objective smoothing in these end areas. A discontinuity in the analysis with re-
spect to all but the uppermost class interval was found to exist between the
chain of Florida Keys and Cape Sable. This was a result of the geographical
features associated with the tip of the Florida peninsula. Gulf storms striking
the southern tip of Florida are generally weaker than those moving from the east
and striking the Atlantic coast of southern Florida and the Keys. Treatment of
this area was discussed in Section 6.2.1.
7.3 Results
An inspection of Figures 34 and 35 reveals that there is an overall increase in
central pressure from south to north, a well-known fact, caused, in part, by
decreasing water temperature toward the north. Distinct minima ranked in order
from lowest pressure at the 5-percent level are found on 1) the tip of the
Florida peninsula, 2 ) at the Texas-Mexico border, 3) near Louisiana's Mississippi
Delta, 4) at the South Carolina-North Carolina state line, and 5) over the
southern New England coast.
The primary maximum occurs near the (until recently) sparsely populated coastal
area west of Cross City, Florida (mile 1,100 in fig. 34). Secondary maxima lie
near the mouth of Delaware Bay (mile 2,400 in fig. 3 5), and near Jacksonville,
Florida (mile 1,800 in fig. 3 5). The Jacksonville maximum exceeds the Delaware
Bay maximum for the higher percentile levels. Pressures also rise northward
along the upper New England coast.
Reasons for the increase in central pressure from south to north include the
entrance of colder and drier air at low levels, which destroys the upward slope
of the isotherms from outside to inside the circulation and decreases the
amount of energy available to the storm. According to Riehl (1954), jet streams
at high levels which are detrimental to tropical cyclones are stronger and more
common in temperate latitudes. Riehl states that "the arrival of the equatorward
margin of a westerly jet stream at high levels will destroy a [tropical cyclone]
circulation rapidly since it favors upper convergence, entrance of cold air
aloft, subsidence, and drying."
7.3.1 Pressure Minima
7.3.1.1 South Florida Minimum. The lowest accepted sea-level barometer reading
(892.3 mb) , not including tornadoes, in the Western Hemisphere occurred at Long
Key, Florida, in the hurricane of September 2, 1935. This contributed to the
south Florida minimum.
89
3c±3AVTJJ —
sxawris -
nOOVSN3d -
ixoia
3n=W0 2W^
>ClS3AlW
TSVSIldua
3
e
•J u
C -(
n cq
« 3
2 o
— S-
u a
SO °
5 «
a aa
- (0
-J U
3 C
4) V
y y
«
1)
3 *J
o
o
<M
o
a>
CD
c qui ) 3^nss2ad
ja a s
U, 35 "3
T 8
<?>«■ —
I
o
3J O _
m 3> e
3 — —
80*-/ 3
yj
90
iao<iiSV3
xaOA a/om —
stohlwh
NDiSTfcftHC -
cq^) 3anss3dd
91
7.3.1.2 South Texas Minimum. Hurricane Beulah (92 3 mb) , the third most intense
storm (in terms of P ) included in this study, struck the Port Isabel area of
Texas in September 1967. Hurricane Carla (931 mb) and the Galveston hurricane of
September 1900 (936 mb) , two other notably severe hurricanes, struck the Texas
coast between Matagorda and Galveston Islands. There is no reason why Carla or
the Galveston storm would not have been at least as strong if they had struck the
south Texas coast. If we look at storms outside the bounds of the main area of
interest in this study, Hurricanes Janet and Allen also lend strong support for
the south Texas minimum. Janet brought a P of 914 mb to Chetumal, Mexico (18°N)
in September 1955 (Dunn et al. 1955). Allen had the lowest central pressure
(899 mb) ever observed in the western Caribbean while passing through the Yucatan
Channel on September 7, 1980 (see append. A).
7.3.1.3 Carolinas and Southern New England Minima. The two lowest tropical
cyclone central pressures observed along the coasts of Georgia, South Carolina,
North Carolina and Virginia, occurred during the passage of Hurricane Hazel
(1954) and Helene (1958). Hazel struck the coast near the North Carolina-South
Carolina state line. Helene aimed her winds at the same area but turned away to
the northeast a few hours before the center would have made landfall. In the
Carolinas and in southern New England where the coast projects eastward, there is
increased exposure to north-northeastward moving cyclones, some of which, like
Hazel and Helene, can be of great intensity.
7.3.1.4 Mississippi Delta Minimum. This minimum was caused principally by
Hurricane Camille (1969), and its effect is most prominent in the lower
percentiles. Even though Camille passed east of Louisiana on her way to the
Mississippi coast, the minimum appears near the mouth of the Mississippi River
because this portion of the coast is further south (lower latitude). The data at
the 1-percent level indicate a well-defined minimum; the analysis of the
5-percent curve in Figure 3 4 was lowered to provide continuity with the 1-percent
curve.
7.3.2 Pressure Maxima
7.3.2.1 Cross City, Florida, Maximum. The lowest central pressure recorded in a
hurricane entering the northern Gulf coast of the Florida peninsula was 958 mb in
the storm of September 1950, which entered the coast near Cedar Key. This is not
nearly as low as hurricane central pressures observed on the mid-Gulf coast
(Mississippi, Alabama, and the Pensacola area) and on the southwest coast of
Florida to the south. Is an extremely low P here less likely clima tologically
or is this simply a sampling variation during the period of record? Present
indications suggest that there is a real variation and the 1- through 15-percent
curves in Figure 34 reflect this judgment.
Our judgment was based on the following. A good many storms have paralleled
the west coast of Florida close to shore from the Keys northward. Although the
eyes of these hurricanes remained over water, substantial amounts of air entering
the storm at the surface had trajectories over the Florida peninsula. Miller
(1963) has shown that sensible heat is lost from a parcel of air as it travels
overland. His calculations for Hurricane Donna (1960) show that the surface
inflow over land is essentially a moist adiabatic process, which leads to the
hypothesis that, since the major portion of the eastern semicircle of an
alongshore west Florida hurricane is over land, a portion of the storm's surface
latent and sensible heat source is removed, the equivalent potential temperature
92
of the surface air is lowered, and the radial gradient of equivalent potential
temperature at the surface is weakened. Movement of a storm out of tropical
waters can further weaken the gradient. The Labor Day hurricane of 193 5 is a
good example of what can happen when an intense hurricane leaves the Florida Keys
and heads up the west coast of Florida. After crossing Long Key with a central
pressure of 892.3 mb (2 6.3 5 in.), the hurricane brushed Cape Sable and paralleled
the west coast of Florida for about 30 hours before entering the coast near Dead
Mans Bay. By then, the storm had weakened to minimal hurricane intensity. The
air mass north of the hurricane and surface water temperatures had remained
essentially constant as the storm skirted no more than 50 nmi off the coast for
those 30 hours.
Although the area has not experienced a severe storm in over 100 years, it
should be noted that the Cross City area is exposed to hurricanes moving in from
the southwest. For a storm moving from this direction, the land effect would not
be significant. For example, a hurricane could develop over the Bay of Campeche,
attain great strength over the central Gulf, and then aim its destructive winds
directly at the area as in the storm of October 1842 (Ludlam 1963). Figure 34 is
intended to combine these possibilities.
7.3.2.2 Delaware Bay Maximum. The strongest tropical cyclone to move inland on
the New Jersey coast during this century was a minimal hurricane (Sept. 1903)
with central pressure above 982 mb. Storms heading north-northeastward over the
Delmarva peninsula after having entered the coast at a point farther south are
more common, but these storms have usually filled to a considerable degree by the
time they reach Delaware Bay. The raw data have been deliberately undercut in
the Delaware Bay area because our method of data analysis is more sensitive to
landf ailing storms than to bypassing storms. Most of the hurricanes affecting
this part of the coast pass offshore before striking or bypassing the southern
New England coast, but it is possible that they could turn into the Delmarva-New
Jersey coast. These storms have central pressures comparable with landfalling
storms of southern New England. Therefore, in an attempt to provide the best
estimate of the underlying population and to ensure consistency along this
section of the coast, the curves for the Delaware Bay area reflect both the raw
data and the possibility of more intense storms striking the coast.
7.3 .2 .3 Jacksonville Maximum. The P probabilities achieve another high point
along the northeast coast of Florida. Again, the shape of the coastline has an
effect. The direction of the coastline is from 160° to 340° (measured from
north) in this region. When a storm recurves sufficiently to miss the southeast
coast, it usually misses the northeast coast. Until 1964, the city of
Jacksonville was unique in that it was the only major city on the Atlantic coast
south of Connecticut that had never sustained winds of hurricane force in modern
times. Hurricane Dora spoiled this fortuitous record in September 1964, lashing
the Jacksonville area with 82-mph winds and demonstrating that Jacksonville was
not immune from hurricanes.
7,3*2.4 Northern New England Coastal Maximum. P Q rises steadily going from
southeastern Massachusetts northward to Canada. The "cold wall" of the Labrador
Current contributes to this effect. During August, the month of warmest sea-
surface temperatures, water temperatures average between 65° and 70°F from Long
Island to Cape Cod. Along the coast of Maine during the same month, the
temperature is in the upper 50 's - cold enough to give any tropical cyclone an
extratropical character.
93
8. RADIUS OF MAXIMUM WINDS
8.1 Analysis
Cumulative frequencies of R's included in Tables 1 through 3 for the same
overlapping zones, centered 50 nmi apart, as used for the P analysis were
analyzed. R's for southern Florida were treated in the same way as pressure.
The same hurricanes were used for both P and R. For each 400- or 500-nmi
coastal segment, the R values were plotted on cumulative frequency graphs. The
percentages were determined by the plotting position formula (see sec. 7.2 and
append. C). Examples of the frequency analysis for specific coastal segments are
shown in Figure 3 6. Greater freedom was taken in analyzing the cumulative
frequency curves of R, and the final coastal variation of the probability
distributions, than with P Q , because the R data were considered less reliable.
3ecause data were sparse along the northern portion of the Atlantic coast, the
cumulative frequencies were developed using both landf ailing and bypassing
storms.
account for tropical storms that were not included in the analysis. Tropical
storms, especially weaker ones, often have no well-defined R, and when they do,
it can frequently be as much as a hundred miles from the apparent storm center.
Assigning values of R to such storms would be haphazard, at best. Only
hurricanes (those in tables 1-3) were considered in the frequency analysis of R
along the coast. The R values were determined near the location where P
applies.
100f
I
oi-
./'
!
J-
{
-
I
I
*j
(b)~
t
10
IS
20
29
it
i*
•0
4* 1
RAMUS Of 'iUWM WMM (aHI
Figure 3 6. —Cumulative probability curve of radius of aaximum winds for
hurricanes laodfailing within (a) 2 50 nmi of mlepost 250, near Corpus Christi,
Texas, and (b) 2 00 nmi of milepost 1600, near Vero 3each, Florida.
94
Five discrete probability levels were chosen to portray the results of the
analysis. The coastal variation of R for the Gulf coast and the Atlantic coast
is shown in Figures 37 and 38, respectively. The data along the west coast of
Florida and along the Atlantic coast were limited and were only used to guide
analysis of the final probability distributions. In these areas, the final
results reflect a higher level of meteorological judgment.
8.1.1 Gulf of Mexico
When the five percentiles for each 50-nmi increment along the Gulf coast were
plotted and analyzed, the resulting curves (fig. 3 7) depicted a trend of
increasing R's with latitude, which is consistent with previous studies
(e.g., Weather Bureau (1957), NHRP 33). Data proved to be too sparse to obtain
cumulative frequencies of R for the central Texas coast southward. The five
curves were extended smoothly down the coast to Mexico (about 2 4°N), keeping in
mind that as we proceeded southward along the coast the value of R should not
increase with decreasing latitude.
8.1.2 Atlantic Coast
Cumulative frequency variation of R along the Atlantic coast as shown in
Figure 38 displays increasing R with latitude. There were only eight
observations of R north of Virginia. The smoothing procedure discussed in
Section 6.2.1.1 was not applied for these latitudes; rather, subjective smoothing
was used to extend the curves to the Canadian border.
8.2 Evaluation of the Analysis
Because of a few additional storms and due to revisions made to several R
values previously used in TR 15, our analysis resulted in somewhat different
probability estimates for R than in TR 15. The majority of the revisions were
decreases in R values.
8.2.1 Gulf Coast
8.2.1.1 Florida and Mexico Minima. As mentioned above, there is a variation of
R with latitude, and, as expected, minima occur on both the eastern and western
edges of the Gulf of Mexico portion of Figure 37. For example, with the
exception of Hurricane Camille (1969), an R less than 14 nmi has not been
observed over the central Gulf coast, while four hurricanes with R's less than
14 nmi have affected the western and eastern rims of the Gulf. The analysis
shows moderately lower values on the western rim of the Gulf compared to the same
latitude on the eastern rim and agrees with NHRP 33, which shows the same trend.
8.2.1.2 Mississippi-Florida Panhandle Maximum. The northernmost extension of
the Gulf coast is at Mobile Bay. From what has been discussed so far with regard
to variation of R with latitude, it is reasonable to expect the maximum in this
general area.
8.2.2 Atlantic Coast
The curves in Figure 38 reflect the fact that the radius of maximum winds tends
to increase with latitude between the Florida Keys and Canada. The five probabi-
lity curves attain their greatest slope between coastal Georgia and the Cape
95
8 3
P-FT. MYERS, FLA.
— ST. MARKS, FLA.
<— PENSACOLA, FLA.
— 3IL0XI, MISS.
.AKE CHARLES, LA.
5ALVESTON, TEX.
^— °CRT ISABEL, TEX.
o
(!^u) sgnim wnwixvw jo sniavd
© 50
O =
3> O
96
— 8OST0N. MASS
>>—£ASTPORT. ME.
—NEW YORK, ,N.Y.
— CHARLESTON. S.C.
GAPE HATTSRAS, N.C.
t— OAYTONA 3EACH, FLA.
2 1
X I?
QWU ) 3GNIM wnwixvw jo smcva
97
Hatteras area. It is in these latitudes that hurricanes most often pass from a
tropical to a temperate environment, and it is in this region where one would
expect R to show its greatest increase for the reasons discussed in
Section 8.3. The slope of the lower probabilities curves change less between
Georgia and Cape Hatteras because there are a few storms with small R in the data
sample.
8.3 Radius of Maximum Winds for Intense Hurricanes
Observations indicate that hurricanes with very large R's are of moderate or
weak intensity. In hurricanes moving northward in the Atlantic and becoming
extratropical, R tends to become larger and more diffuse and P generally
rises. Data from intense hurricanes of record (see table 16 and fig. 14)
indicate that the most extreme hurricanes (P less than 92 mb) tend to have
small R's. The question of interdependence of P and R was discussed in Chapter
4. We recommend that an R value of 13 nmi be used for hurricanes with P in the
range of 908-92 mb, and R = 9 nmi be used with P rt less than 908 mb.
9. SPEED AND DIRECTION OF STORM MOTION
9.1 Speed of Storm Motion
Data for the speed of storm motion is discussed in Section 2.5. Included in
these data are a few subtropical storms. We chose to include them since they
also have the ability to produce storm surges.
9.1.1 Forward Speed of Landf ailing Tropical Cyclones
9.1.1.1 Analysis. Cumulative frequencies of forward speed for landf ailing
tropical cyclones were determined for the same overlapping zones used for both P
(sec. 7.2) and R (sec. 8.1). As indicated in Section 2.5, both T and 9 could be
reliably determined for tropical storms as well as hurricanes, thus increasing
the sample size. Cumulative probability curves of forward speeds were determined
using Weibul's plotting position formula (see sec. 7.2). Figure 39 shows
examples of the cumulative frequency analysis of raw data at two points along the
coast (near Corpus Christi, Texas and Vero Beach, Florida). Percentage values at
each 50-nmi location were determined from analyses such as Figure 39 for 5-, 20-,
40-, 60-, 80- and 95-percent levels. The values were then analyzed to ensure
consistency along the coast. The resulting curves are shown in Figures 40 and
41.
9.1.1.2 Results and Discussion. Figures 40 and 41 show that tropical cyclone
speed generally increases with northward progression of each storm, especially
after recurvature to a northerly or northeasterly direction. The upper
50 percent of forward speeds increases from 11-17 kn near Daytona Beach, Florida,
to 35-53 kn at the northern extent of the United States' Aclantic coastline.
Overall, there was a marked increase in values of T along the west coast of
Florida as compared with the variation shown in values of TR 15. In this study,
we omitted hurricanes prior to 1900 that had been used in TR 15. This was done
to ensure a consistent sampling period for all parameters (P , R, T and 9).
Before finalizing this decision, however, we examined the effect of omitting
storms prior to the turn of the century. We found that there were no significant
98
- 60-
10 1S 20 25
?0RWA*D SPEED (kn) FORWAP.0 SPEED (kn)
Figure 39.-- Cumulative probability curve of forward speed of tropical cyclones
landf ailing within (a) 2 50 ™i of ailepost 250, near Corpus Christi, Texas, and
(b) 2 00 nmi of milepost 1600, near Vero Beach, Florida.
differences in the probability distribution of speed for hurricanes by this
truncation of the period of record. TR. 1 5 had based its speed distribution on
hurricanes only. To provide a sample that was consistent with the storms used
for Che direction distributions, and to increase the sample size, the speeds of
tropical storms were used in determining the speed distribution.
The substantial increase in the speeds in the higher percentile levels along
the west coast of Florida (see fig. 40) was due, not to the change in period of
record, but to the addition of tropical storms. Between coastal reference points
900 to 1300, 12 storms with speeds greater than 2 kn were added to the data
sample. All were less than hurricane intensity. Storms that exceed 2 kn at
these latitudes generally have become embedded in a broader-scale circulation
that usually leads to these higher translation speeds. These same oe teorological
conditions involve recurvature, usually into an environment associated with
horizontal temperature gradients that create conditions that are not favorable to
the thermal circulation associated with strong hurricanes (see discussion in
sec. 7.3.2.1). Therefore, the faster translation speeds appear to be associated
with weaker storms. However, the small number of storms and high degree of
99
-^u *navs 3dvo
•"U *SH3AW "li
Id "YIOCIWO'
— ^i^TOCVSHBd
— sw 1x011a
•VI 'S31HVH0 3XV1
•XI 'N01S3A1V9
—XX H39VSI IdOd
_ ^r
_o
o
<M CU — —
(U>1) NOHOW IflUOlS JO Q33dS
"3°
a ** —
^ ? *"
c to
is * J
ab w to
100
-*-vw 'Noisoa
U-AN 'XHOA M3N
—OS 'N01S3iyVHO
i-ON 'SVU311VH 3dVO
CM
o
O
~4-ld *H0V38 VNOIAVQ
-•-"Id llNVIW
(U>j) NOHOW WdOlS JO d33dS
101
variability from storm to storm precluded us from establishing whether a joint
probability relation actually exists, let alone what form the relation might
take. Inclusion of these tropical storms also leads to discontinuities in the
speed distributions between the west and east coasts of southern Florida for all
but the lowest percentiles.
9.1.2 Forward Speed of Bypassing Tropical Cyclones
Observations of bypassing storms are more limited than for those storms
striking the coast, especially for storms from earlier years. Additionally, the
frequency of occurrence of bypassing storms, subject to the criteria in this
study, is lower than for landfalling storms. Given the high degree of natural
variability of tropical cyclones and the limitations just mentioned, we felt it
would be unlikely that we could develop an adequate probability distribution for
the speed of bypassing storms. Consideration of meteorological factors affecting
the speed of storm motion suggests that there is likely to be little difference
in the speed distribution between landfalling and bypassing tropical cyclones.
The speed is primarily dependent on conditions of the larger-scale meteorological
environment. In general, the controlling circulation patterns that affect the
speed are not sensitive to coastal orientation, the factor that leads to the
segregation of landfalling and bypassing storms. We recommend using the speed
distribution for landfalling storms as a reasonable approximation for bypassing
storms*
9.2 Direction of Storm Motion
9.2.1 Direction of Storm Motion for Landfalling Tropical Cyclones
9.2.1.1 Analysis. Tropical cyclone tracks compiled by Cry (1965) and updated
track charts (Neumann et al. 1981) were used in summarizing the directions of
storm motion. Directions of landfalling tropical cyclones were measured at the
time they crossed the coast. Cumulative frequencies of the entry direction for
overlapping 200-nmi zones (100 nmi either side of the central point) were used in
plotting cumulative probability curves at 50-nmi intervals along the Atlantic and
Gulf coasts. In TR 15, cumulative frequencies were counted for overlapping zones
of 75 nmi on each side. In both cases the zones along the coast were smaller
than those used for the other three parameters (P , R and T) because the landfall
directions are totally dependent on coastal orientation which can change
significantly over relatively short intervals. The smaller zones minimized
pooling inconsistent directions. We used storm data since 1900 in the present
study instead of the longer period used in TR 15. We believe the decrease in
sample size due to a shorter observational period is partially compensated by the
increased number of storms taken from a somewhat larger sampling area.
In areas where the coastal orientation changes significantly within 100 nmi of
the point of interest, the direction of entry with reference to the coast was
taken into consideration. For example, a storm that crossed the coast from 2 50°
near Key West would not be counted as a landfalling storm for another point on
the Florida Keys, some distance to the east. In areas where the coastline turns
abruptly, frequency counts were taken over shorter distances. Because of
insufficient data north of Cape Hatteras, analyses there were made over larger
distance increments.
102
105 125 145 195
DIRECTION (dog. Tom north)
35 105 125 145 1 95 195
DIRECTION (dog. Tom north)
direction of aotion of tropical
Figure 42.— Cumulative probability curve of
cyclones landf ailing within (a) 100 nmi of milepost 250, near Corpus Chris ti
Texas, and (b) 100 nmi of milepost 1600, near Vero Beach, Florida.
Cumulative probability curves for direction of storm motion for landfalling
tropical cyclones were constructed using the Weibul plotting position formula
given in Section 7.2. Figure 42 shows examples of these curves for two coastal
locations near Corpus Christi, Texas, and Vero Beach, Florida. Each of the
cumulative probability curves was divided into class intervals, and the values at
selected percentiles were analyzed for three sections along the coast: the Gulf
coast (fig. 43), and the Atlantic coast south (fig. 44) and north (fig. 45) of
Cape Hatteras.
9.2.1.2 Results and Discussion. The direction of landfalling storm motion is
closely related to the coastal orientation curve because the definition of
landfalling restricts the storm direction data selection, exiting and alongshore
storm motions being excluded. Under the influence of the easterly circulation of
the lower latitudes (the Azores-Bermuda high) the tracks of most storms in the
tropics is westward. There is a tendency for these low latitude storms to drift
slowly northward at the western end of the high pressure system. As the storms
drift toward higher latitude, they come under the influence of westerly winds and
recurve northeastward.
103
1 i i r
i — i — i — r
t — i — r
•Id '319VS 3dV0
'Id '3d3AW *ld
•id *s><uvw us
Id VTOCWOVIVddV
•Id 'V100VSN3d
■sw 'ixona
L -^V1 '331HVH0 3W1
—XI 'N01S3A1VO
—XL '13SVSI lHOd
10 « O <o s?
0) CO U) ^. 11)
o
O
O
o
O
O
o
o
o^
CD
CM
CD
sr
O
CO
OJ
CO
^r
ro
ro
C\J
C\J
<M
—
—
o
o
(q;jou wojj. «69p) NOHOW mOlS dO NOI103^ia
104
—ON 'SVa2U.VH 3a?0
#
3* y-\n
a*
w co
o
0) oo
w
MIO
(O
—OS 'N01S3iaVHO
—■79 'xoi/v\SNnaa
U-li 'HCV38 VNOiAVC
■Id 'H0V33 0«3A
— Id 'IWVIW
05 oj
J I L
(i|;jau mo j j. *6ap) NOHOW '/MH013 JO NCHO^yiO
105
25
ia
29
2,
DISTANCE (nmi X I C
Figure 45. — Same as Figure 43, but for Che Atlantic coast north of Cape Hatteras.
As indicated in preceding paragraphs, data sampling for the present analysis
departed slightly from chat used in TR 15. The analvzed results generally agree
with Che previous study. On Che Gulf coast, 50 percent of Che scorns occurring
between coasCal reference points 900 and 1300 anpeared Co have greater southerly
and easterly components than previously determined in TR 15. This difference may
be attributed Co Che data samples of different time oeriods. Thirty-four storms
occurring prior to 1900, with directions from 200 to 270° were not included in
Che present analysis.
9.2.1.2 (a) Gulf coast Figure 43 shews smoothed profiles at selected oer-
centiles for direction of moCion for landfalling tropical cyclones for the Gulf
coast. As expected, Che tropical cyclones striking Che west coast of Florida
come from the souChwesC direction and those striking Che Texas coasC are
generally from Che southeast. Along the mid-Gulf, coastal areas are vulnerable
to storms approaching from both southeast and southwest.
106
9.2.1.2 (b) East coast, south of Cape Hatteras. Figure 44 confirms that for
la ndf ailing storms near Miami, Florida, the predominant direction of storm motion
is from the east or southeast. In the vicinity of Daytona Beach, Florida, there
is higher percentage of landfalling storms coming from the south and southeast.
North of the Florida-Georgia state line, the percentage of north to
northeastward moving storms increases gradually northward, which reflects the
increasing number of recurving storms. This group of landfalling storms
includes recurving tropical cyclones of Atlantic origin and storms that exited
the Florida coast and may have reentered the coast south of Cape Hatteras. More
than 50 percent of the landfalling tropical cyclones near Cape Hatteras are
north-northeastward moving storms.
9.2.1.2 (c) East coast, north of Cape Hatteras. For the period since
publication of TR 15 (1974-84), only two storms made landfall north of Cape
Hatteras. The directions of motion for these two storms were consistent with
those used in TR 15. Given the very small number of storms affecting this part
of the coast, we believe that no changes to the earlier analysis were necessary
for this stretch of the coast. Figure 45 has been taken from TR 15 for areas
north of Cape Hatteras, North Carolina. The stretch of coast south of Cape
Henry, Virginia, is vulnerable to landfalling tropical cyclones coming mainly
from the easterly directions; the coastal orientation excludes the northeastward
moving storms from the landfalling category. Tropical cyclones striking this
part of the coast from the northeast have generally been weak. Figure 45 also
reveals that tropical cyclones striking the coast east of New York consist mostly
of northward to northeastward moving storms.
9.2.1.3 Areas of Discontinuous Direction Profile. The directions of landfalling
storm profiles along the east coast are not continuous in the vicinity of Cape
Hatteras, North Carolina and Cape Cod, Massachusetts, because of abrupt turning
of the coast. The probability distribution of landfalling storm direction and
its relation to P and T for Cape Hatteras area was discussed in Section 5.4.
For the Cape Cod area, it is advisable to use the direction distributions from
the south and west of the eastern extremity of the cape (lower milepost
number), since the maximum wind region of a hurricane lies to the right of the
hurricane track. The values indicated for Cape Sable (fig. 43) may be used as
representative for hurricanes striking the mainland coast of Florida Bay.
9.2.2 Direction of Storm Motion for Bypassing Tropical Cyclones
Bypassing storms, by definition, do not strike the coast in the vicinity of
interest. Variation of coastal orientation and the restriction imposed by the
definition make specification of a generalized distribution of directions
impossible. For practical computations, we recommend assigning a direction
parallel to a tangent to the coastal point of interest for bypassing storms, with
the general motion from east to west along the Gulf coast facing south, and for
coasts such as Texas, Florida and along the Atlantic, the general direction
should be from south to north.
107
10. ADJUSTMENT OF HURRICANE INTENSITY FOR FILLING OVERLAND
10.1 Introduction
The tropical cyclone is a thermally driven circulation in which the vertical
flux of sensible and latent heat is the primary source of energy for both its
formation and maintenance. One of the factors that diminishes hurricane
intensity is the increased dissipation of kinetic energy by friction overland.
In a steady-state hurricane, the frictional dissipation of kinetic energy near
the core of a hurricane is approximately balanced by the energy supplied by
sensible and latent heat. Overland, the heat sources are greatly reduced or may
be lacking altogether. Hence, the energy balance between heat and frictional
dissipation is upset after the hurricane moves overland. It has been suggested
by Bergeron (1954) and Palmen (1956) that the removal of the sensible heat source
(hence also the removal of the latent heat source) is the most important factor
which contributes to the filling process overland. Miller (1963) confirmed the
earlier work of Bergeron (1954) and others in stating that filling stems
principally from the reduction of equivalent potential temperature (0 ) of the
rising air around the hurricane core. Miller also noted that filling due to
surface friction was of minor importance compared to the removal of the oceanic
heat source.
Palmen and Newton (1969) state that "Owing to the removal of the oceanic heat
source in the inner region, the baroclinity is reduced since the air ascending in
the inner cloud wall now has somewhat lower 9 . As a result, the outward radial
e
wind component in upper levels is reduced. The previous balance between the mass
inflow is thus temporarily disturbed and pressures rise."
In this chapter the term "filling" is used in the generally accepted sense. As
discussed by Petterssen (1956), filling of a center of low pressure refers to an
increase in the central pressure. Petterssen further distinguishes deepening and
filling from intensification and weakening: while the former terms apply to the
pressure, the latter apply to the pressure gradient. Changes in intensity or in
pressure gradients are not dependent entirely on changes in central pressure.
Nevertheless, it has been generally assumed that there is a high degree of
correlation between the two factors (e.g., Hess 1945). Recent studies on inner
core structure of mature hurricanes generally support this assumption. Most of
the studies on Atlantic hurricanes based on reconnaissance flight data since the
1940's have focused on the inner core region (within 1° latitude radius). There
is a scarcity of upper air data between 2-3° from the center. Frank and
Gray (1980) used compositing techniques to determine an average radius and
frequency of 30-kn winds around tropical cyclones. Merrill (1984) found no
significant correlation of the radii of outer closed isobars with core intensity
in a comparison of large and small tropical cyclones. Weatherford (1985)
examined flight-level wind data obtained by reconnaissance aircraft flown into
tropical cyclones in the northern Pacific during the period 1980-82. She showed
that the outer strength (as measured by the magnitude of winds between 1°- and
3°-latitude radius of the storm center) is highly correlated with the extent of
30-kt surface winds, while the core intensity was a far more variable feature.
10.2 Index for Overland Filling
In defining clima tological hurricane parameters for this study, we assumed a
steady-state hurricane moving on a constant course during the time period
required for storm surge computation. Strictly, these assumptions cannot be
108
carried through to determine a filling rate for hurricanes over land. However,
transient phenomena of the hurricane core will not be considered. After the
center of a hurricane crosses the coast, the hurricanes' central pressure rises
faster than the change in peripheral pressure and the pressure deficit
decreases. The decreasing intensity of the hurricane affects the level of storm
surge, especially in bays and estuaries. It has been shown that the coastal
surge and the surge producing forces in bays and estuaries vary proportionally
with pressure deficit (e.g., Harris (1959), Ho and Myers (1975)). These
surge-producing forces in bays and estuaries are, mainly, the propagation of open
ocean surge into the bay and wind setup. The open coast storm surge increases
with increasing kinetic energy of the wind which acts on the water surface, other
factors being held constant. In a mature hurricane, the kinetic energy of the
wind is approximately proportional to the pressure deficit. Hence, the coastal
surge and the propagation of the open coast surge into a bay are approximately
proportional to the pressure deficit in a hurricane. The second major factor in
the bay and estuary response is wind setup. The magnitude of the wind setup
effect is also proportional to the kinetic energy of wind for given conditions
and, thus, is also approximately proportional to the concurrent pressure deficit.
Having considered the cause and effect of filling of hurricanes, it is logical
to select pressure deficit as an index in defining the rate of filling
overland. The advantages in selecting such an index is its direct and simple
application to numerical surge models. Its application is, however, restricted
because the averaging process used in the analyses tends to ignore the
extremes. Recognizing that wind profiles in individual hurricanes do not always
vary with the change in central pressure, the resultant rate of filling is best
utilized in an idealized hurricane model. The user is cautioned against using an
average filling rate for individual hurricane case studies for the purpose of
replicating storm surge levels, especially in bays and estuaries.
10.3 Previous Observational Studies
Hubert (1955) observed that filling is most pronounced in the innermost region
of the hurricane. Malkin (1959) stated that both filling and decrease in
intensity proceed at a lesser rate when the ratio of water to land of the
underlying surface increases along the track. Malkin analyzed the change in
central pressure after landfall of 13 selected hurricanes and evaluated the
average change in pressure gradient after landfall. Schwerdt et al. (1979)
analyzed eight selected hurricanes which occurred during the period 1957-70 with
central pressure less than 949 mb. They accepted the previous data and analyses
made by Malkin and developed the filling rates in terms of reduction in wind
speed for 3 different zones along the Gulf and Atlantic coasts of the United
States. Jarvinen et al. (1985) suggested a quadratric filling rate of central
pressure for hurricanes along the Texas coast and stated that the largest
intensity changes occurred in the most intense storms within the first 6 hours
after landfall.
10.4 Analysis of Data
In this chapter, the decrease in hurricane intensity after landfall was
determined by using the ratios of pressure deficits at specified times after
landfall (AP ) and the pressure deficit at the time of landfall (AP ). The
109
pressure deficit was obtained by subtracting the central pressure (P Q ) from the
peripheral pressure (P n )» These ratios give the percentage decrease in intensity
and, thus, a rate of filling for hurricanes overland.
In order to determine the pressure deficit, an analysis of P and P must be
made for the duration of the storm over land. Values of P n were estimated from
3-hour ly weather maps. For P , graphs were constructed showing sea-level pressure
readings from stations with available continuous pressure records during the time
period when a hurricane approached and passed by that station. These pressure
readings and corresponding distances from the storm center were used in composite
pressure-distance profiles analyzed at 3-hour intervals for a duration of
24 hours after landfall. These profiles were then extrapolated to the storm
center, yielding estimated central pressures at various times.
Observations are taken at regular reporting stations as well as by many private
individuals and corporations for their own uses. In some cases, this material is
filed with the National Climatic Data Center (NCDC), NOAA's Cooperative Reporting
Network. Additionally, after many severe storms, surveys are made to obtain
supplementary data that are not routinely collected. With improvement of the
observational network, analyses of observed data have proven to yield fairly good
estimates of central pressure. These analyses, supplemented by analyzed synoptic
Available data were plotted and a profile was fit to the data by eye. This
allowed meteorological considerations to influence the resulting profiles.
Figure 46 is an example of central pressure-time profiles for Hurricanes
Frederick (1979) and Alicia (1983). Both hurricanes struck the Gulf coast;
Frederick made landfall near the Alabama-Mississippi state line, while Alicia
entered the coast just south of Galveston, Texas.
10.5 Filling Rates by Region
Table 19 shows a list of selected hurricanes which were analyzed individually
to estimate the decrease in hurricane intensity after landfall. The data sample
of 23 hurricane events was separated into three groups, based on the location
where each hurricane crossed the coast. These regions are shown in Figure 47.
Region A is the area along Gulf coast from Port Isabel, Texas, to Apalachicola ,
Florida, region B, the coast of Florida south of 29°N, and region C, the Atlantic
coast from South Carolina to Rhode Island. Hurricane Camille, listed with other
hurricanes in region A, was both intense and small in size, and had the steepest
filling rate within the first 6 hours after landfall. Its central pressure rose
from 909 mb to 965 mb in 6 hours, an average increase of more than 9 mb per
hour. Camille stands out as a special case, presumably representative of the
most intense storms. Since our hurricane sample indicates that there is a
tendency for the more intense hurricanes to fill more rapidly, we have chosen to
provide separate filling rates for extreme hurricanes.
For region A, filling rates were determined for each of the six Gulf hurricanes
since 1971, following the procedures outlined in Section 10.4. Figures 48 a and
b show the variation with time after landfall of filling rates of hurricanes
listed in part A of Table 19. The filling rate is the ratio of pressure deficit
at specified times (t) after landfall (AP ) to the pressure deficit at the time
of landfall (AP ), or AP /AP . The filling rate for Hurricane Camille was
adopted from analyses made in an earlier study (Schwerdt et al. 1979). Filling
110
1005
I
! 1
I 1 | " ~
S
995
-
jgS*
LU
985
-
^**r _
3
CO
CO
LU
lT
Q.
975
_o
LU
>
LU
965
<
LU
955
jT
• PRESSURE - OISTANCE PROFILES
STATION PRESSURE
945 C
1
' 1
(a)
i i i
9 12
TIME fhr)
15
13
1000
1 990
980
970
960 -
-
!
1
1
1 I 1
■„.**%
-
^S*
-
/
-
• PRESSURE-DISTANCE PROFILES
& RECONNAISSANCE AIRCRAFT
STATION PRESSURE
(b)
!
i
1
1 i 1
12
TIME Chr)
Figure 46. — Pressure profiles after landfall for (a
September, 1979 and (b) Hurricane Alicia, August, 1983.
1 3
Hurricane Frederick.
Ill
Figure 47. — Map showing geographical regions used Co study filling rates.
L 12
Table 19. — Selected landf ailing hurricanes (192 8-1983) used to estimate overland
filling rates.
No. of
Storms
Hurricane
State of
Landfall
Region
11
Aud rey
Carla (
Betsy (
Camille
Celia (
#Edith (
•/Carmen
#Eloise
//Frederi
#Allen (
//Alicia
(1957)
1961)
1965)
(1969)
1970)
1971)
(1974)
(1975)
ck (1979)
1980)
(1983)
Louisiana
Texas
Louisiana
Mississippi
Texas
Louisiana
Louisiana
NW Florida
Mississippi-Alabama
S. Texas
Texas
(Gulf coast from
Apalachicola, FL
westward)
Sept. 17, 1928
Sept. 15, 1945
Aug. 27, 1949
Donna (1960)
S. Florida
S. Florida
S. Florida
S. Florida
(Florida
south of 29°N)
Sept. 21, 193 8
Sept. 15, 1944
Carol (1954)
Hazel (1954)
Gracie (1959)
Donna (1960)
//Belle (197 6)
#David (1979)
New York
New York
New York
North Carolina
South Carolina
New York
New York
Georgia
(Atlantic coast
from South Carolin,
northward)
# Indicates storms since 1971
rates for other hurricanes prior to 1971 determined by Schwerdt et al. were
checked for consistency by using observed minimum pressure data as previously
discussed. Minor changes were made whenever warranted.
The filling rates at selected time intervals for the 11 hurricanes listed in
Table 19 for region A were averaged to develop a filling rate for hurricanes of
lesser intensity. Separate filling rates for more intense hurricanes were
estimated by taking into consideration this average filling rate and the extreme
filling rate associated with Camille. Intense hurricanes were arbitrarily
defined as storms with AP greater than 85 mb, which have approximately the same
intensity as category 5 hurricanes according to the Saf fir/Simpson scale
(Saffir 1977)
Figure 49 shows the filling rate curves for hurricanes with AP.
less than or equal to 85 mb, AP equal to 100 mb, and AP equal to 110 mb. These
curves have been used to develop the pressure deficits in part (a) of Table 20.
Linear interpolation between values in Table 20 should be used instead of
recourse to Figure 49 to assure a higher degree of accuracy and consistency.
113
11
CD
&
\ Tx
\ A V x*
\ \ \\ x.
X \ \ \ x
\ *V x X
\ \\ ^ x
"
x \\ x \
x\\ \\
-
Xv X >\
\\ \
\
1
I'll!
X i-
XV5i
! 1^
- cvJ
-co
-CO
CM
rO
lO
CD
CO
CD
*dv
OliVd
115
22.
oiiva
U -j
•x -
s
i "o
u —
- 2
116
Table 20. — Changes in hurricane pressure deficits due to overland filling
Time After
Landfall
(hr) Pressure Deficit (mb)
(a) Gulf hurricanes, west of Apalachicola, Florida
40 60 80 85 90 95 100 105 110
2
34
51
68
72
76
78
80
81
82
4
30
44
59
63
66
67
68
69
70
6
26
40
53
56
58
59
60
61
62
8
22
34
45
48
50
51
52
53
54
10
20
30
40
42
44
45
46
47
47
12
18
27
36
38
39
40
41
41
42
14
16
24
32
34
35
36
36
36
36
16
14
21
28
30
31
32
32
32
32
18
12
19
25
26
27
28
28
28
28
(b) Florida hurricanes, south of 29°N
40 60 80 85 90 95 100 105 110
38 57 75 80 85 88 90 91 92
36 54 70 75 79 81 82 83 84
6 34
51
67
71
75
76
77
78
79
8 32
48
63
67
71
72
73
74
75
10 30
45
59
63
67
68
69
70
71
12 28
42
56
60
63
64
65
66
67
14 26
40
53
56
59
60
61
62
63
16 25
37
50
53
55
56
57
58
59
18 24
35
47
50
52
53
53
54
55
(c) Atlantic
hurricanes, north of
Georgi a-Sou th
Carolina
state
line
40
60
80
85
90
95
100
105
110
2 36
54
72
76
81
86
90
94
99
4 32
49
65
68
73
77
81
85
89
6 28
44
58
61
65
68
72
76
79
8 25
39
51
54
57
60
64
67
70
10 22
34
44
47
50
53
56
59
61
12 19
29
38
41
43
46
48
51
53
14 17 25 34 36 38 40 42 44 46
16 15 22 30 31 33 35 37 39 ' 40
18 13 19 26 27 29 30 32 34 35
117
<]|<3 ' 6
Figure 50, — Comparison of filling rates for various hurricanes crossing the
Florida peninsula and Che filling curve for region B from Schwerdt
ec al. (1979).
There were no additional storms that affected region B since 1971. The average
filling rate curve determined by Schwerdt et al. (1979) was adonted after
checking for consistency by comparing A? t /A? ratios for several hurricanes. Mo
attempt was made to obtain separate filling rate curves for each of these
hurricanes because data was scanty. Figure 50 shows a plot of these ratios at
various times after landfall and the filling rate curve for region B from
Schwerdt et al. It is again recommended that filling rates be obtained from the
values in Table 20b by linear interpolation. Figure 51 shows filling rate curves
for selected oressure deficit levels in region B.
Figure 52 shows the filling rate at various times after landfall for Hurricane
Hazel (1954) and Gracie (1959). These two hurricanes entered the Atlantic coast,
crossed the Carolinas, and recurved towards the north. Filling rates for a 12-hr
period after landfall are shown in the figure because both hurricanes became
extratropical soon after that period of time. The changes in intensity during
their extratropical stage would not be representative of hurricanes. Only the
rate of weakening for the first 12-hr period, as indicated by the solid line, was
used in this analysis. Figure 52 also shows the rate of weakening for Hurricane
David (1979) after entering the coast just south of Savannah, Georgia. The
obvious difference between the curves reveals that David had a much slower
113
119
Ol<3 - 6
Figure 52. — Variation with tine after landfall of filling rates for Hurricanes
Hazel (1954), Gracie (1959), and David (1979).
filling rate than those of Hazel and Gracie. This can be partially explained by
che fact that David traveled inland, parallel Co the coast, with half of the
cyclonic circulation of che storm remaining over water. The heat supply from the
underlying sea acted to minimize the filling process. For this reason, David was
not used in obtaining an average filling rate for Atlantic coast hurricanes.
Figure 53 shows a plot of filling rate versus time after landfall for
hurricanes which crossed the shores of Long Island, New York and the New England
states. Data obtained during the first 12-hr period after landfall were used in
Che analysis because Chese hurricanes were fast moving storms. In a 12-hr period
after landfall, they would have either moved across the United States border into
Canada or become extratropical. The average filling rates for these hurricanes
agree fairly well with the filling curve for Hurricanes Hazel and
Gracie (fig. 52). Combining both sets of data, we obtained the average filling
curve as shown in Figure 54. Since region C has not experienced any extreme
hurricanes, this curve was adopted to represent the filling rates of landfalling
hurricanes of all intensities in this region. Again, linear interpolation from
Table 20 should be used to determine pressure deficits.
120
<3l<3
<
1.0
6 8
TIME Chr)
Figure 53. — Variation with tiae of filling races for New England hurricanes.
10.6 Results
The lower filling rate curves for regions A and 3 in Figures 49 and 51 ara
applicable to hurricanes with pressure deficits less Chan or equal to 85 mb at
the time of landfall. For hurricanes with pressure deficits greater than 35 mb,
filling rates may be obtained from interpolation of pressure deficit values given
in Tables 20a and 20b for regions A and B, respectively. There is no separate
filling rate determined for hurricanes of the most intense category in region C.
12 1
122
The filling rate for region C, shown in Figure 54, was extended to depict
filling up to 18 hr after landfall, for consistency. One should realize that the
degree of accuracy decays with increasing time after landfall. The curve for
region C is also applicable to areas north of Long Island, New York in order to
include the entire coastline.
Assuming that the rate of filling is linear for the first 10-hr period after
landfall, we can draw a straight line joining the point indicating the filling
rate at 10 hr after landfall and the point of origin for each of the three
regions. We obtained slopes of .051, .075, and .056 for regions A, B, and C,
respectively. Linear interpolation of the slopes may be used as an aid to
develop intermediate curves in estimating appropriate filling rates for areas
lying between designated regions.
11. APPLICATION OF HURRICANE PARAMETERS
11.1 Introduction
An objective of this report has been to define climatological probability
distributions of hurricane central pressure (P Q ), radius of maximum winds (R),
forward speed (T), and direction of motion (9) along the Atlantic or Gulf coasts
of the United States. In some applications of these data — for example, in flood
insurance studies — it would be necessary to calculate frequency distributions
of hurricane-induced surges on the coast by combining the analysis of hurricane
climatology with the application of a numerical storm-surge model. Also needed
in such application is the overall frequency with which hurricanes enter the
coast in terms of strikes per mile per year, or some equivalent unit, within
certain discrete distances. The landfall point of a hurricane is another
parameter needed in a surge-frequency analysis. If storm track is parallel to
the coast, then distance from the coast is needed instead of direction. This
chapter outlines procedures to be followed in selecting hurricane parameters,
their corresponding probabilities, and the representative storm tracks and
frequencies for surge-frequency analyses as currently adopted in flood insurance
studies.
11.2 Landfall Point
The cyclonic wind field of a hurricane usually increases from the edge of the
storm to the highest value at the radius of maximum winds (R) then rapidly
decreases to low values near the center. There is usually some asymmetry to the
approximately circular pattern, with the highest winds on the right side as the
storm moves forward. From the geometry of the hurricane wind field pattern, the
maximum shoreward component is experienced at a given coastal site when the
hurricane center landfalls approximately at distance R to the left. On a
straight coast with uniform bathymetry, the highest surge along the coast will be
experienced at this point of highest wind. Variable bathymetry can modify this
location somewhat. Similarly, a bay experiences the strongest winds from a
hurricane of given intensity and lateral extent when the storm track is about at
distance R to the left of the center of the bay, as viewed from the sea.
In addition to the inverse barometer effect and the convergence of wind
affecting surge levels near a storm's center, the major driving force for coastal
surges is the stress of the wind on the water, roughly proportional to the square
of the wind speed. Average wind profiles show that surface winds of a hurricane
123
at a distance five times the radius of maximum winds (5R) from the storm center
are less than half of its maximum magnitude (Schwerdt et al. (1979), chapt. 13)
and the magnitude of the corresponding peak surge heights are only about
2 5 percent of the peak. Except for the most intense storms, hurricane-induced
surges of any significant level would not affect the coast if the hurricane made
landfall at a distance exceeding 5R to the left of the point of interest or at a
distance of more than 3R to the right. The distance 3R is chosen because coastal
surge heights drop off much more rapidly to the left of the landfall point.
11.3 Peripheral Pressure
The linkage between the climatologically-def ined hurricane central pressure
(P Q ) and the pressure deficit (AP) used in a storm-surge model is the peripheral
pressure (P n )« p n is used to compute the pressure deficit (AP = P - P ), which
is a measure of the intensity of a hurricane. P is frequently considered the
average pressure around the hurricane where the isobars change from cyclonic to
anticyclonic curvature. This pressure occurs at a distance from the storm center
near where storm inflow begins and, therefore, has physical meaning. In this
study, P is used in conjunction with clima tologically determined hurricanes.
The use of a climatological mean value for P is considered adequate for this
purpose.
Schwerdt et al. (1979) described several techniques for evaluating P and
indicated that there is no significant variation of P with latitude. They
compiled peripheral pressures for Gulf and Atlantic coast hurricanes with P less
than 982 mb since 1900. The average value of these given peripheral pressures is
1013 mb. We recommend that this climatological mean value be adopted as a
representative peripheral pressure to compute pressure deficits in storm-surge
frequency analysis.
11.4 Probability Distributions of Hurricane Parameters
and Frequency of Occurrence
This chapter describes the application of hurricane parameters needed to
calculate storm surge levels on the coast. The assessment of probability
distributions of these parameters assumes a steady-state hurricane moving on a
constant course during the time period required for storm-surge computations. The
averaging process along the Gulf and Atlantic coasts assures a smooth continuous
variation of individual parameters along the coast. Exceptions to these basic
assumptions and specific treatment of discontinuities have been discussed in
preceding chapters. These include frequencies of landfalling tropical cyclones
for the Florida Keys (sec. 6.2), refinements in alongshore hurricane track counts
and probability distributions of landfalling storms for the North Carolina coast
(sec. 5.4), frequencies of exiting storms (sec. 6.3), and filling of storms as
they pass overland (chapt. 10). The procedure to estimate probability distribu-
tions of hurricane parameters for exiting storms will be discussed further in
subsequent paragraphs.
The probability distribution of P is determined for landfalling tropical
cyclones (sec. 7.3). There is no reason to believe that the pressure distribution
of alongshore storms would be different from that of landfalling storms because
both classes of storms experience an area with climatologically similar atmos-
pheric and sea-surface conditions. Hence, this probability distribution of P
can also be applied to alongshore storms. The probability distribution of R is
124
assumed to be the same for the landf ailing, bvpassing and exiting categories of
storms. Probability distributions for direction and speed of storm motion for
landfalling storms are given in Chapter 9. For alongshore storms, the direction
is, by definition, assumed to be parallel to the coast and the probability
distribution of forward speed is assumed to be the same as for landfalling
hurricanes.
The frequency of tropical cyclone occurrence is defined as the number of tracks
per year per nautical mile of a smoothed coast for each of the landfalling and
exiting categories of storms (chapt. 6). Figure 27 depicts variation of
frequencies of landfalling tropical cyclones along a smooth coastline. We have
implicitly smoothed out the coast while smoothing out the accidental landfalling
points of storms. A stretch of the coast that turns sharply in a direction
almost parallel to that of the predominant storm motion is less exposed than
adjacent coastal segments more normal to the track direction. For areas where
the coast turns abruptly, such as the Mississippi Delta, Apalachee Bay, and the
tip of Florida, special consideration must be given in using the generalized
results in this report. An example of the treatment of a discontinuity in land-
falling storm frequencies at Cape Hatteras, North Carolina, is discussed in
Section 5.4. In areas where variations of frequencies along the coast are large,
the effects of the steep gradient of hurricane frequencies along the coast on
resultant coastal surge frequencies must be considered (see examples given in the
following section).
For alongshore hurricanes, the bypassing distance is a significant parameter
instead of the landfalling point discussed in Section 11.2. The frequency of an
alongshore hurricane event is treated in the same way as the landfalling storms,
except that the frequency is defined as the number of storms per year passing
through a given distance interval along the line perpendicular to the coast. It
is the counterpart of the frequency per year for landfalling storms multiplied by
the length of coastal segment, determined by the spacing of storm tracks for
computations. The application of this is further discussed in the following
section. Figures 3 1 and 32 depict the variation along the Gulf and Atlantic
coasts of tropical cyclone tracks bypassing the coast at sea. These figures give
accumulated track count at selected intervals from the coast. With this
information, plots of the cumulative count of tracks versus distance from the
coast can be constructed for any coastal point. Figure 55 is an example of the
accumulated track count plotted against distance from the coast for Vero
Beach, Florida. The difference in accumulated track count between two points
read off the graph gives the number of storms, per 100 years, crossing the given
distance interval. It is advisable to use small distance intervals near the
coast, using the selected R values for landfalling storms as a guide. This would
ensure that the effect of maximum winds on coastal waters would maximize
generated surge levels.
The frequency of tropical cyclones bypassing the coast overland is not treated
as such in this report. First, these storms tend to weaken after traversing over
land and the surge frequencies resulting from these storms are usually not
significant (see for example fig. 29). Second, the contribution of this class of
storms to surge frequencies varies greatly in different localities. Coastal
surges of significant levels can be produced by such storms in areas near the
Outer Banks of North Carolina and in the southern portion of the Florida
peninsula. For the treatment of this class of storms in North Carolina, the
reader is referred to the report by Ho and Tracey (1975). The North Carolina
12 5
40 60 80
DISTANCE FROM COAST (nmi)
Figure 55. — Plot of cumulative count of alongshore storms versus distance from
coast for Vero Beach, Florida {milepost 1600).
12 6
study mav be used as a .guide for the Florida peninsula area. A good example of
these storms in Florida is the hurricane of October 1950 which entered the coast
of south Miami and moved north-northwestward over the entire length of the
peninsula. Its intensity weakened to that of a tropical storm after passing near
Orlando, Florida. Another hurricane that entered the southern tip of Florida and
weakened rapidly while moving northward is the hurricane of 193 5. It was the
most intense Atlantic hurricane ever recorded (P = 892 mb while crossing the
Florida Keys). It weakened to minimal hurricane intensity (P = 960 mb) by the
time it crossed the northern Florida coast, near 30°N. Hurricanes that move
northward over the Florida Peninsula seem to fill faster than hurricanes that
cross the peninsula in a east-west duration. It should be noted that the filling
rate in Chapter 10 for Florida should not be applied to this class of northward
moving hurricanes. The treatment of such tropical cyclones passing the coast
inland needs further investigation.
11.5 Applications of Profiles of Probability Distributions
for Hurricane Parameters
Hurricane parameters for storm-surge frequency computations can be obtained by
constructing cumulative probability curves for each of the hurricane parameters
from smoothed alongshore graphs. Table 2 1 itemizes the information needed by the
user. Items 1-4 are information to be listed for identification. Item 5 lists
the meteorological information needed for surge-frequency computations and where
it can be found in this report. Numerical values to be filled in (5a through 5 j )
are hurricane parameter values for designated percentiles and frequencies read
from the appropriate figures for the location (milepost) listed in Item 4. Using
these values for the designated percentiles, the full range of individual
parameters of clima tologically possible hurricanes that can make landfall at the
point of interest can be determined. The cumulative probability curve, thus
obtained, is then divided into class intervals that can be used in frequency
computations.
In storm-surge frequency analysis, landfall points should be selected by taking
into consideration the lateral extent of the coast affected by an individual
hurricane. Based on the geometry of the hurricane wind field, as discussed in
Section 11.2, we recommend that the coastal area of influence for the purpose of
surge computations be limited to a distance 5R to the left and 3R to the right of
the point of interest. Hurricane tracks crossing landf ailing points at 10-2 5 nmi
intervals should be considered in estimating overall surge levels. The computed
peak surge at the point of interest for a given storm passing along each of the
selected hurricane tracks is assumed to be representative of a "surge event" that
could occur within the distance interval (10-2 5 nmi) between two landf ailing
points. Hence, the selection of track spacing should be guided by (1) the
alongshore gradient of the bathemetry, (2) the storm size and (3) the
configuration of coastal areas. For example, tracks spaced at larger distance
intervals may be specified for a straight coastline with uniform bathymetry while
computation for storms crossing landf ailing points at close intervals would be
needed to produce representative surge levels on the shorelines of bays and
estuaries. To obtain the frequency of this "surge event" multiply the frequency
of landfalling storms (storms/nmi/yr, given in item 5h of table 2 1) by the
selected distance interval between landfalling points.
127
Table 21 — Summary sheet of information needed from this report for surge-
frequency computations
1. Geographic location
2. Latitude
3. Longitude
4. Milepost [fig. 1]
5. Hurricane parameters
Central pressure (P ) [fig. 35]
Pressure deficit (1013-P Q )
Forward speed (T) [fig. 41]
Direction (9) [fig. 44]
Coastal orientation
Angle of approach (d-e)
Radius of maximum winds (R) [fig. 38]
Percentile
1
5
15
30
50
70
90
Percentile
5 1 20
40
60
80
95
1
Percentile
5
16.67
50
83.33
95
h. Frequency of landfalling storms
[fig. 27]
i. Frequency of exiting storms
[fig. 28]
storms/10 nmi/100 yr, or
storms/nmi/yr
storms/10 nmi/100 yr, or
storms/nmi/yr
j. Frequency of alongshore storms (accumulative counts) [fig. 32]
Distance from
coast (nrai)
Frequency
(storms/100 yr)
Frequency
(storm/yr)
Frequency within
distance interval
10
20
30
50
75
100
128
After completing the appropriate number of forms for the coastal area of
interest, the information can be used to reconstruct cumulative probability
curves for the parameters that describe the clima tologically possible hurricanes
for each of the selected locations. Intermediate cumulative probability curves,
if required, may be estimated using linear interpolation. The reconstructed
cumulative probability curves will provide values for any selected percentile
within the full range of individual parameters. Intermediate curves will insure
a smooth transition from one location to the next.
Table 22a is an example of a completed computation form for storm-surge
frequency analysis at Vero Beach, Florida (milepost 1600). Tables 22b and 22c
contain similar information for locations located 50 nmi to the north and south
of Vero Beach, respectively. Figure 56 shows a plot of cumulative probability
curves of P for the three locations. Curves for intermediate locations can be
determined by linear interpolation. It should be noted that the lowest 1 percent
of P for Vero Beach and the lowest 2 percent of P for the location 50 nmi to
the south (fig. 56) fall into the intense hurricane category. As discussed in
Section 4.5, these hurricanes should have an assigned R of 13 nmi. Similarly,
cumulative probability curves can be plotted for the other parameters.
Figure 55 shows a plot of cumulative frequency of bypassing hurricane tracks
versus distance from the coast for Vero Beach. The accumulated track counts for
selected distances from the coast are taken from Item 5j of Table 22a. A smooth
line was then drawn by eye joining the data points. From this curve, the
frequency of bypassing storms within the first 10 nmi of the coast is 0.0170
storms/yr, the number of storms passing the distance interval of 10-30 nmi is
(0.0575-0.0170) 0.0405 storms/yr and the track count for the distance interval of
30-75 nmi is (0.1600-0.0575) 0.1025 storms/yr. Similarly, frequencies within
other distance intervals may be obtained (e.g., table 23).
The next step in determining hurricane probabilities requires that the hurri-
cane parameters be divided into class intervals for the landfalling storms and
that the mid-point value of each class interval be determined. The size and
number of intervals cannot be specified a priori, but must involve judgment that
considers factors that can vary from site to site; an example for P is given in
Figure 57. It should be noted that Figure 57 shows only the fraction of all
hurricanes with intensities below certain levels and makes no reference to
frequency in terms of events per year. For storm-tide frequency computation,
this continuous distribution could be divided into five class intervals, each
represented by the pressure deficits at the mid-point of the class interval.
This computational probability distribution is indicated by the dashed line on
Figure 57. For computation purposes, the hurricanes are treated as if the most
severe 1 percent all had pressure deficits of 95 mb, the next 6 percent had a
deficit of 84 mb, the next 12 percent a deficit of 70 mb, the next 40 percent a
deficit of 45 mb and the last 41 percent a deficit of 19 mb. These class
intervals are representative values and their corresponding probabilities are
listed in Table 23. It is of interest to note that these class intervals are not
equally spaced. Closer intervals are used for parameters associated with intense
hurricanes. Higher surge levels produced by the intense hurricanes contribute to
the 100-yr or higher tide frequencies. Similarly, cumulative probability curves
for other parameters can be divided into class intervals, and values for
designated percentiles are listed in Table 23.
129
Table 22a — Summary sheet for Vero Beach, Florida
27° 39» N
80° 27' w
1600
1. Geographic location
2. Latitude
3 . Longi tude
4. Milepost [fig. 1]
5. Hurricane parameters
Central pressure (P ) [fig. 35]
Pressure deficit (1013-P )
Forward speed (T) [fig. 41]
Direction (9) [fig. 44]
Coastal orientation
Angle of approach (d-e)
Radius of maximum winds (R) [fig. 3<
Vero Beach, Florida
Percentile
1
5
15
30
50
70
90
921
93 1
94 5
958
977
990
997
92
82
68
55
36
23
16
Percentile
5
20
40 | 60
80
95
3.5
6.5
8.5
10.6
13.0
16.3
Percentile
5
16.67
50
83.3 3
95
055
087
118
13 5
153
020
020
020
02
020
03 5
067
098
115
133
5.5
11.0
18.0
28.0
37.0
h. Frequency of landf ailing storms
[fig. 27]
i. Freemen cy of exiting storms
[fig. 23]
0.76
storms/10 nmi/100 yr, or
0.00076 storms /nmi/yr
1 .2 storms/10 nmi/100 yr, or
0.0012 storms/nmi/vr
j. Frequency of alongshore storms (accumulative counts) [fig. 32
Distance from
coast (nmi)
Frequency
(storms/100 yr)
Frequency
(storm/vr)
Frequency within
distance interval
10
1.70
0.0170
0.0170 (0 - 10 nmi)
20
3 .3
0.033
0.0160 (10- 20 nmi)
30
5.75
0.0575
0.0245 (2 0- 30 nmi)
50
10.00
0.1000
0.042 5 (3 0- 50 nmi)
75
16.00
0.1600
0.0600 (50- 75 nmi)
100
2 4.00
0.2 400
0.0800 (75-100 nmi)
130
Table 22b — Summary sheet for 50 nmi north of Vero Beach, Florida
1. Geographic location
2 . Latitude
3 . Longi tude
4. Milepost [fig. 1]
5. Hurricane parameters
Central pressure (P ) [fig. 35]
Pressure deficit (1013-P Q )
c. Forward speed (T) [fig. 41]
d. Direction (0) [fig. 44]
e. Coastal orientation
f. Angle of approach (d-e)
g. Radius of maximum winds (R) [fig. 38]
Vero Beach + 50 nmi
28° 30*
N
80° 42'
W
1650
Percentile
1
5
15
30
50
70
90
92 5
93 5
949
963
981
991
997
88
78
64
50
32
22
16
Percentile
5
20
40 60
80
95
3.8
6.8
8.8
11.0
13.2
16.5
Percentile
5
16.67
50
83.33
95
044
076
115
131
153
000
000
000
000
000
044
076
115
• 131
153
6.3
11.5
19.0
28.8
37.5
h. Frequency of landfalling storms 0.74 storms/10 nmi/100 yr, or
[fig. 27]
0.00074 storms /nmi/yr
1.65 storms/10 nmi/100 vr, or
i. Frequency of exiting storms _ _
[fig. 28]
0.00165 storms /nmi/yr
j. Frequency of alongshore storms (accumulative counts) [fig. 32]
Distance from
coast (nmi)
Frequency
(storms/100 yr)
Frequency
(storm/yr)
Frequency within
distance interval
10
1.3 6
0.0136
0.013 6 (0 - 10 nmi)
20
2.41
0.02 41
0.0105 (10- 20 nmi)
30
4.32
0.0432
0.0191 (20- 30 nmi)
50
8.2 5
0.082 5
0.0393 (3 0- 50 nmi)
75
14.10
0.1410
0.0585 (50- 75 nmi)
100
22 .60
0.2260
0.0850 (75-100 nmi)
131
Table 22c — Summary sheet for 50 miles south of Vero Beach, Florida
1. Geographic location
2 . Latitude
3 . Longi tude
4. Milepost [fig. 1]
5. Hurricane parameters
Vero Beach
50
26° 54' N
80° 11» W
1550
Percentile
Central pressure (P ) [fig. 3 5'
Pressure deficit (1013-P )
Forward speed (T) [fig. 41]
Direction (9) [fig. 44]
Coastal orientation
Angle of approach (d-e)
Radius of maximum winds (R) [fig. 3.
1
5
15
30
50
70
90
916
92 7
941
955
974
989
996
97
86
72
58
39
24
17
Percentile
5
20
40
60 1 80
95
3.4
6.4
8.5
10.5 1 12 .8
16.2
Percentile
5
16.67
50
83.33
95
059
093
12
142
155
020
020
02
020
02
039
073
100
122
13 5
5.0
10.0
17.5
28.0
37.0
h. Frequency of landfalling storms
[fig. 27]
i. Frequency of exiting storms
[fig. 28]
0.97
torms/10 nmi/100 yr, or
0.00097 storms /nmi/yr
0.90 storms/10 nmi/100 yr, or
0.00090 storms /nmi/yr
j. Frequency of alongshore storms (accumulative counts) [fig. 32]
Distance from
coast (nmi)
Frequency
(storms/100 yr)
Frequency
(storm/yr)
Frequency within
distance interval
10
2 .34
0.0234
0.023 4 (0 - 10 nmi)
20
4.02
0.0402
0.0168 (10- 2 nmi)
30
7.10
0.0710
0.0308 (20- 30 nmi)
50
12.50
0.1250
0.0540 (3 0- 50 nmi)
75
18.50
0.1850
0.0600 (50- 75 nmi)
100
25.80
0.2580
0.0730 (75-100 nmi)
132
10
._ — '*
-
20
■
30
-
-
s~\
'//
-a
;/'
°
40
</'
-
j
* '/'
5
* /'
'/;
Ll_
50
-
UJ
f At— Vero Beach
3
Vero
Beach + 50-*//
LU
/ //
(V
60
/ //
-
D
CO
//'
/ //
10
/ //-*- Vero Beach-50
—J
70
7 /'
-
Q_
/ //
t / '
' / '
80
' / '
' / *
f / /
90
/
/ J
/ /
/
™
/
i
/
100 1
J I i l
1 5 10 20 30 40 50 60 70 80 90
EXCEEDANCE PROBABILITY
95 97
■99
Figure 56,-- Cumulative probability curves of ? for designated locations.
The parameters adopted for Vero Beach, Florida, in Table 23 represent five
pressure deficit categories, four R categories, three T categories and three
9 categories. These factors are considered statistically independent except that
the four R's are not the same for all pressure deficit categories, a small value
being used with the class interval of most intense pressure deficits in line with
the discussion in Section 4.5. Thus, in Table 23, the most intense hurricanes
(1 percent of total count) are assumed to have an R of 13 nmi. The R's for
weaker storms cover the full range of values. For these storms, the R class
intervals need not be equally spaced. One needs to consider an appropriate class
interval for the critical range of R near 3 nmi. This is because of the
importance of the dynamic effect of winds near R on the surse calculation. For a
hurricane with constant intensity crossing the continental shelf of average
width, the induced peak surge reaches its maximum value for R at or slightly
greater than 30 nmi. Similarly, there exists a critical motion relative to a
coast that gives the highest possible surge under any given set of conditions.
The critical speed generally is greater than 2 5 kn. Thus, the fastest moving
storms, especially if they are large and moving directly toward the coast, pose
the greatest hazard. Appropriate class intervals should also be designated for
133
Table 23. — Tropical cyclone parameters Vero Beach, Florida
P AP
(mb) (mb)
R
(nmi)
T
(kn)
9 L
(deg.)
Pe
Landf ailing
918
95
0.01
*
5.7
0.30
040
0.16
929
84
0.06
11.0
0.333
9.5
0.40
088
0.40
943
70
0.12
18.0
0.333
14.0
0.30
112
0.44
968
45
0.40
28.0
0.333
994
19
0.41
Landf ailing storm frequency = 0.00076 storms /nmi /yr.
* R = 13 nmi is assigned a probability of 1.0 for P < 920 mb.
Exiting
950
63
0.07
13.8
0.5
8.8
0.5
067
1.0
961
52
0.12
23.5
0.5
18.0
0.5
980
33
0.40
999
14
0.41
Exiting storm frequency = 0.0012 storms/nmi/yr ,
('nmi)
(storms/vr)
Alongshore
R p r T
(nmi) (kn)
5.0
0.017
13
.5
7.0
.5
P , AP, and P i are
the same as those
15.0
0.016
25
.5
12.3
.5
25.0
0.024
for landfalling
40.0
0.042
storms
62.5
0.060
Central pressure (mb)
Pressure deficit (mb)
Proportion of total storms with indicated AP value
Distance from center of storm to principal belt of maximum winds (nmi)
Proportion of storms with indicated R value
Forward speed of storm (kt)
Proportion of storms with indicated T value
Direction of entry or exit, measured clockwise from the coast (deg.)
o
AP =
p i =
R =
p r :
^:
Li
Pq = Proportion of storms with indicated 9, value
L = Distance of storm track from coast (nmi)
F = Frequency of storm tracks crossing a line normal to coast
(storm tracks /yr passing through the interval centered at L)
134
SO 40 20
PRESSURE DEFICIT (rnb)
Figure 57. — Cumulative probability curve for pressure deficit at
Beach, Florida. Dashed lines shown selected class intervals.
Vero
Che critical range of speed and direction. The direction of approach, 88°, was
selected (table 23) to represent the most critical ranee of directions which
would oroduce the highest coastal surge if other factors were the same.
In Table 23, the most intense landf ailing hurricane class interval (1 percent
of the total) is assumed to have an R of 13 nmi and one third of each class of
less intense hurricanes are assumed to have R's of 11, 18, and 2 5 nmi. The ?
and R categories for landfalling storms given in Table 23 define 13 different
hurricanes [ 4 (?) Q X 3(R) + (P = 918 and R = 13)]. The probability of each of
these is obtained by multiplying the respective probabilities in the table. The
sum of the probabilities of the 13 hurricanes, of course, eauals 1. P and R are
statistically independent of d and T. Thus, the parameters for landfalling storms
defines 117 different hurricanes (13 X 3(T) X 3(9)). Each of the 117 discrete
storms represent a portion of the probability domain, the probability of each
135
storm is obtained by multiplying the four parameter probabilities. For example,
the probability of having a hypothetical hurricane with P = 92 9 mb, R = 18 nmi,
T = 9.5 kn, and 9 L = 88°, is 0.0032 (0.06 X 0.333 X 0.4 X 0.4).
11.6 Exiting Tropical Cyclones
The intensity of exiting storms generally decreases because the overland tra-
jectory reduces the energy supply (see chapt. 10). Central pressure data observed
over the ocean in landfalling and alongshore storms may not be used to estimate
the probability distribution of P Q for exiting storms. Because of insufficient
data sample size, no attempt was made to construct cumulative probability curves
of hurricane parameters for exiting storms based on observed data.
As previously indicated (sec. 6.3.2.3), exiting storms normally contribute
little to the overall frequencies of storm surges, except for the Florida
peninsula. Storms exiting the east coast of Florida frequently come from the
southwest. Plots of cumulative probability curves of landfalling direction along
the west coast of Florida show a median direction of about 22 7° (from north)
along most of the coast. The median direction for storms crossing the Florida
peninsula from the Atlantic to the Gulf varies from 110-13 0° (from north). The
typical translation speed of these storms is about 10 kn (see figs. 40 and 41).
Using the median landfalling direction on the opposite coast, and assuming that
the storm direction remains constant as it crosses the peninsula, a
representative overland storm track can be determined for exiting storms. The
next step is to estimate the time it takes the storm to cross the peninsula,
using the median landfalling speed, which is also assumed constant. This time can
be used to determine 'filling-rate factors (sec. 10.5) that can be applied to the
P distribution at the landfall point. The modified P distribution is then used
o o
to approximate the P distribution for exiting storms.
Except for P we assume that there are no changes in other parameters as
storms crossed the Florida peninsula. Cumulative probability curves developed for
R, T, and at the point of landfall are applicable to storms exiting the
opposite coast. For expediency and economic considerations it will usually be
sufficient to assign two class intervals for each of the R and T distributions
and four intervals for P (e.g., see table 23). The direction of storms exiting
the east coast of Florida may be represented by 22 7° from north since the range
of probable direction of exit is so small. Two class intervals for directions of
storms exiting the west coast of Florida are recommended by assigning 50 percent
probability each to the directions of 073° and 116° from north. Because of
infrequent occurrence of storms exiting north of Tampa Bay on the west coast of
Florida, it should not be necessary to attempt to define exiting storm parameters
to the north of this point.
12. SUMMARY AND DISCUSSION
This report presents an analysis of the geographical distribution of major
hurricane and tropical storm factors useful for flood insurance studies. Each of
these factors influences the ability of the storms to produce storm tides. This
report provides a climatology of hurricane factors needed for surge-frequency
analyses and information useful for storm-surge modeling. Because our purpose
was to develop clima tological data in a probabilistic sense, judicious smoothing
136
Table 24. — Data used in this report for probability analyses
Clima tological
Characteristic
Data
Source
Application
Figures
Storm frequencv Tropical cyclone tracks
(landfalling. of the North Atlantic
alongshore, Ocean, 1871-1984
exiting)
Tropical cyclones
27, 28
31, 32
Central
pressure
Radius of
maximum winds
Tables 1 to 3 (hurricanes
with P Q <982 mb since 1900)
Tables 1 to 3 (hurricanes
with P Q <982 mb since 1900)
Tropical cyclones 34, 35
Direction and Tropical cyclone tracks of
speed of forward the North Atlantic Ocean,
motion 1900-84, 'HURDAT' tape
Hurricanes
Tropical cyclones
37, 3!
40, 41, 43
44. 45
Cumulative probability curves for central pressure, based on hurricane data,
were extended to include tropical storms.
was employed along the Atlantic and Gulf coasts and across the frequency spectra
to eliminate the effect of sampling fluctuations. Results of our analyses are
given in figures and tables with brief definitions and explanations. The figures
depicting coastal profiles of probability distributions for selected percentiles
give ranges of clima tological ly defined hurricane parameters. Users should
determine for their particular application the critical class intervals within
these ranges.
Table 2 4 summarizes the data sources and the classes of tropical cyclones
represented. These are not the same for the all factors, for the reasons stated
in the report.
12.1 Frequency of Tropical Cyclone Occurrences
The frequency of landfalling, exiting, and bypassing tropical cyclones were
summarized in Figures 27, 28, 3 1 and 32, respectively. Of the three classes of
storms, the most significant factor for storm-surge frequency computations is the
frequency of landfalling storms. Coastal variation of landfalling storm
frequencies is most rapid along the Atlantic coast of Florida and along the North
Carolina and Virginia coasts (fig. 27). This steep gradient of hurricane
frequency contributes to the potential for significant differences in the
magnitude of resultant coastal surge frequencies in adjacent locations along
these portions of the coast. Frequencies of alongshore storms are generally
small (negligible) for most of the Gulf coast and, except for portions of the
west coast of Florida, contribute little to the overall tide frequencies. High
frequencies of exiting storms occurred on the Atlantic coast near Jacksonville,
Florida and just north of Cape Hatteras. Exiting storms generally produce lower
storm surges and they are usually weaker than landfalling or alongshore storms
137
for the same latitudes. Their contribution to the overall storm-surge
frecuencies is negligible in most cases. Because of coastal orientation,
frequencies of landf ailing storms are not continuous from Cape Sable, Florida, to
the Florida Keys. Our treatment of the analysis in this area is discussed in
Section 6.2 .
12.2 Probability Distribution of Storm Parameters
Analysis of the data led to a set of graphs depicting the probability
distribution of central pressure, radius of maximum winds, forward speed, and
direction of storm motion. The central pressure distribution (figs. 34 and 3 5)
is for tropical cyclones and is broken down for illustrative purposes into seven
probabilit-z levels (percentiles) ranging from 1 to 90 percent. The probability
levels were selected at intervals sufficiently close for the purpose of
reconstructing smooth cumulative probability curves and should not be considered
as a guide in selecting the number of class intervals appropriate for
computational purposes.
Probability levels ranging from 5 to 95 percent were selected to depict the
full range of other parameters (R, T, 9). The distribution for the radius of
maximum winds (figs. 37 and 38) was derived from hurricane data only, and is
illustrated for five selected probability levels. The resulting probability
distribution may be considered applicable for both hurricanes and tropical
storms. The forward speed distribution (figs. 40 and 41), based on tropical
cyclones landfalling on the United States coasts, is illustrated for six selected
probability levels. This distribution is also adopted for alongshore storms, as
discussed in Section 11.4. The direction of storm motion distribution for
landf ailing tropical cyclones is illustrated for five probability levels in
Figures 43 (Gulf) and 44 (Atlantic coast, south of Gape Hatteras). Because of
the very limited number of storms affecting the Atlantic coast north of Cape
Hatteras, only three probabilitv levels are given for direction of storm motion
for this portion of the coast (fig. 45).
12.3 Independence of Parameters
The parameters presented in this study can be considered statistically
independent, exceot for central pressure (P_) and radius of maximum winds (R).
Limited historical data indicate that hurricanes with central pressure below
920 mb have small R's. Hurricanes with large R's are nearly always of moderate
or weak intensity, but not all the weaker storms have large R's. Establishing
the joint probability of two factors with a degree of reliability racuires a much
larger sample of data than that available in Tables 1 to 3 . For this reason, we
specify R values for only the most intense hurricanes (sec. 4.5).
Observations show that alongshore hurricanes generally move at a faster speed
than landfalling hurricanes at the same latitude. The differences in forward
speeds (T) were presumably related to the direction of storm motion, 9,
(according to TR 15). There was no detectable interrelation between T and 9 for
landfalling hurricanes found in statistical tests of the present study. The
small sample size does not allow us to establish any interrelation between T and
9 for alongshore storms. With increased data in future years, it would be of
interest to re-examine this rela tionshio.
133
It is generally believed that hurricanes striking the Florida Keys from an
easterly direction are more intense than hurricanes coming from the southwesterly
direction. The data sample for that area is not sufficient for us to
statistically establish an interrelation of P and for landfalling storms. A
similar situation exists in the area north of Cape Hatteras, North Carolina. In
the latter case, separate P probability distributions were evaluated for
tropical cyclones coming from the northeasterly and southeasterly directions (see
chapt. 5). Segregating the sample into subgroups would take care of the inter-
dependence of P and 9 for this particular area. This approach may be used to
deal with similar problems in other regions.
ACKNOWLEDGMENTS
The authors are grateful for the help of numerous members of the Water
Management Information Division, Office of Hydrology, National Weather Service,
during the course of this study. In particular, we would like to thank Helen V.
Rodgers for invaluable editorial assistance, and Roxanne Johnson who ably
prepared many of the figures for this report. The guidance and critical review
of the manuscript by E. Marshall Hansen, Chief of the Water Management Division,
was especially helpful.
We would like to thank researchers at the National Hurricane Center, the
Hurricane Research Division of NOAA's Atlantic Oceanographic and Meteorological
Laboratories, and the National Weather Service's Techniques Development
Laboratories for their extremely helpful discussions, both during the formative
stages of our study, and as work progressed. We also want to thank Dr. Gerald F.
Cotton of NOAA's Air Resources Laboratory, who advised us on some statistical
procedures.
The authors especially want to express their appreciation to the staff of the
Hurricane Research Division for providing us with data from their files. In
particular, we wish to thank Mark D. Powell for sharing with us his data
collections obtained in post-hurricane surveys, and Neil Dorst for preparing
computer plots of hurricane wind data observed by reconnaissance aircraft.
Periodic meetings with the staff of the sponsoring agency, the Federal
Emergency Management Agency, and their consultants, provided us with additional
insight throughout the preparation of this report. Dr. Frank Tsai of the Federal
Insurance Agency, Federal Emergency Management Agency, Dr. Chester P. Jelesianski
of the Techniques Development Laboratory, and Charles Neumann of the National
Hurricane Center, provided crucial reviews of drafts of this report. These
reviews were most helpful in improving the quality of the final product.
139
REFERENCES
Alaka, M.A. , 1968: Climatology of Atlantic Tropical Storms and Hurricanes, ESS A
Technical Report WB-6, Environmental Sciences Services Administration, U.S.
Department of Commerce, Washington, DC, 18pp.
Benson, M.A., 1962: Plotting Positions and Economics of Engineering Planning,
Proceedings of American Society of Civil Engineers , 88 (HY6), part 1.
Bergeron, T. , 1954: The Problem of Tropical Cyclones, Quarterly Journal of the
Royal Meteorological Society , Vol. 80, No. 344, pp 131-164.
Bradbury, D.L., 1971: The Filling Over Land of Hurricane Camille, Satellite and
Mesometeorology Research Project Paper No. 96, NOAA Grant E-198-68(B) MOD
No. 2, Department of the Geophysical Sciences, The University of Chicago,
Chicago, IL, 2 5 pp.
Case, R.A. and Gerrish, H.P., 1984: Atlantic Hurricane Season of 1983, Monthly
Weather Review , Vol. 112, No. 5, pp. 1083-1092.
Chow, V.T. (ed.), 1964: Handbook of Applied Hydrology , McGraw-Hill, New York,
NY.
Clark, G.B. and Staff, 1984: Annual Data and Verification Tabulation - Atlantic
Tropical Cyclones, 1983, NOAA Technical Memorandum NWS NHC-2 1 , National
Hurricane Center, National Weather Service, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, Miami, FL, 92 pp.
Cline, M., 192 6: Tropical Cyclones , McMillan Company, New York, NY, 301 pp.
Colon, J. A. , 1953: A Study of Hurricane Tracks for Forecasting Purposes, Monthly
Weather Review , Vol. 81, No. 3, pp. 53-66.
Conover, W.J. , 1971: Practical Non-parametric Statistics , John Wiley and Sons,
New York, NY, 462 pp.
Craddock, J.M., 1969: Statistics in the Computer Age , American Elsevier
Publishing Company, New York, NY, 214 pp.
Cry, G.W, 1965: Tropical Cyclones of the North Atlantic Ocean, Tracks and
Frequencies of Hurricanes and Tropical Storms, 1871-1963, Technical Paper
No. 55, Weather Bureau, U.S. Department of Commerce, Washington, DC, 148 pp.
DeAngelis, R.M. , 1969: Enter Camille, Weatherwise , Vol. 22, pp. 173-179.
DeAngelis, R.M. and Nelson, E.R., 1969: Hurricane Camille August 5-22,
Climatological Data National Summary , Vol. 2 0, No. 8, Environmental Science
Services Administration, U.S. Department of Commerce, Washington, DC,
pp. 451-474.
DeAngelis, D. , 1979: Hurricane David - Preliminary Report, Weekly Weather and
Crop Bulletin, National Oceanographic Data Center, Environmental Data and
Information Service, National Oceanic and Atmospheric Administration,
Washington, DC, pp. 16-17.
140
Dunn, G.E., Davis, W.R., and Moore, P.L. , 1955: Hurricanes of 1955, Monthly
Weather Review , Vol. 83, No. 12, pp. 315-326.
Frank, W.M. and Gray, W.M., 1980: Radius and Frequency of 15 m/s (30 kt) winds
around tropical cyclones. Journal of Applied Meteorology , Vol. 19, pp 219-223.
Friedman, H.A., Brown, W.J., Jr., and Michie, J.D., 1982: Airborne Research
Meteorological Data Collected by the National Hurricane Research Laboratory
During the NOAA/RFC WP-3D ERA - Inventory and Availability, NOAA Data Report
ERL A0ML-2 , National Hurricane Research Laboratory, National Oceanic and
Atmospheric Administration, U.S. Department of Commerce, Miami, FL, 376 pp.
Friedman, H.A. , Armholes, C.A., Dorst, N.M. , Nelson, C.J. , and Brown, W.J. , Jr.,
1984: Airborne Research Meteorological Data Collected by the National
Hurricane Research Laboratory (HRD/AOML) During the 1982-1983 Hurricane Seasons
- Inventory and Availability, NOAA Data Report ERL AOML-3 , National Hurricane
Research Laboratory, National Oceanic and Atmospheric Administration, U.S.
Department of Commerce, Miami, FL, 158 pp.
Garcia, A.W. and Flor, T.H. , 1984: Hurricane Alicia Storm Surge and Wave Data,
Technical Report CERC-84-6, Coastal Engineering Research Center, Waterways
Experiment Station, U.S. Army Corps of Engineers, Vicksburg, MS, 89 pp.
Graham, H.E. and Nunn, D.E., 1959: Meteorological Considerations Pertinent to
Standard Project Hurricane, Atlantic and Gulf Coasts of the United States,
National Hurricane Research Project Report No. 33, Weather Bureau, U.S.
Department of Commerce, Washington, DC, 76 pp.
Graham, H.E. and Hudson, G.N. , 1960: Surface Winds Near the Center of Hurricanes
(and other cyclones), National Hurricane Research Project Report No. 39,
Weather Bureau, U.S. Department of Commerce, Washington, DC, 200 pp.
Gumbel, E.J. , 1958: Statistics of Extreme Events , Columbia University Press, New
York, NY.
Hardy, A.V. and Carney, C.B., 1962: North Carolina Hurricanes, Weather Bureau,
U.S. Department of Commerce, Raleigh, NC, 2 6pp.
Harris, D.L. , 1959: An Interim Hurricane Storm Surge Forecasting Guide.
National Hurricane Research Project Report No. 32, Weather Bureau, U.S.
Department of Commerce, Washington, DC, 2 4 pp.
Hawkins, H.F., Christensen, F.E., Pearce, S.E., and Staff, 1962: Inventory, Use
and Availability of National Hurricane Research Project Meteorological Data
Gathered by Aircraft, National Hurricane Research Project Report No. 52,
Environmental Research Laboratories, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, Boulder, CO, 48 pp., plus data.
Hebert, P.J. and Poteat, K.O., 1975: A Satellite Classification Technique for
Subtropical Cyclones, NOAA Technical Memorandum NWS SR-83 , National Weather
Service, National Oceanic and Atmospheric Administration, U.S. Department of
Commerce, Fort Worth, TX, 2 5 pp.
141
Hebert, P.J. , 1980: Atlantic Hurricane Season of 1979, Monthly Weather Review ,
Vol. 108, No. 7, pp. 973-990.
Hebert, P.J. and Staff, 1980: Annual Data and Verification Tabulation Atlantic
Tropical Cyclones, 1979, NOAA Technical Memorandum NWS NHC 13, National
Hurricane Center, National Weather Service, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, Miami, FL , 77 pp.
Hess, S.L. , 1945: A Statistical Study of the Deepening and Filling of
Extratropical Cyclones. Journal of Meteorology , Vol. 2, No. 3, pp. 179-184.
Ho, F.P. and Myers, V.A., 1975: Joint Probability Method of Tide Frequency
Analysis Applied to Apalachicola Bay and St. George Sound, Florida. NOAA
Technical Report NWS 18, National Weather Service, National Oceanic and
Atmospheric Administration, U.S. Department of Commerce, Silver Spring, MD,
43 pp.
Ho, F.P., Schwerdt, R.W. , and Goodyear, H.V. , 1975: Some Clima tological
Characteristics of Hurricanes and Tropical Storms, Gulf and East Coasts of the
United States, NOAA Technical Report NWS 15, National Weather Service, National
Oceanic and Atmospheric Administration, U.S. Department of Commerce, Silver
Spring, MD, 87 pp.
Ho, F.P. and Tracey, R.J., 1975: Storm Tide Frequency Analysis for the Coast of
North Carolina, North of Cape Lookout, NOAA Technical Memorandum NWS HYDRO-2 7,
National Weather Service, National Oceanic and Atmospheric Administration, U.S.
Department of Commerce, Silver Spring, MD , 46 pp.
Ho, F.P. and Miller, J.F., 1982: Pertinent Meteorological and Hurricane Tide
Data for Hurricane Carla, NOAA Technical Report NWS 32 , National Weather
Service, National Oceanic and Atmospheric Administration, U.S. Department of
Commerce, Silver Spring, MD , 111 pp.
Ho, F.P. and Miller, J.F., 1983: Pertinent Meteorological Data for Hurricane
Allen of 1980, NOAA Technical Report NWS 35, National Weather Service, National
Oceanic and Atmospheric Administration, U.S. Department of Commerce, Silver
Spring, MD, 73 pp.
Howell, G. , Lee, D.Y. , and Wang, H. , 1982: Storm Surge Measurements and
Computations for Hurricane David, Coastal and Oceanographic Engineering
Department, University of Florida, for Office of Nuclear Regulatory Research,
U.S. Nuclear Regulatory Commission, Washington, DC, 67 pp.
Hubert, L.F., 1955: Frictional Filling of Hurricanes. Bulletin American
Meteorological Society , Vol. 36, No. 9, pp. 440-445.
Jarvinen, B.R., Neumann, C.J., and Davis, M.A.S., 1984: A Tropical Cyclone Data
Tape for the North Atlantic Basin, 1886-1983: Contents, Limitations, and Uses,
NOAA Technical Memorandum NWS NHC 22, National Hurricane Center, National
Weather Service, National Oceanic and Atmospheric Administration, U.S.
Department of Commerce, Coral Gables, FL, 2 1 pp.
142
Jarvinen, B.R., Damiano, A.B., and Locke tt, G.J., 1985: A Storm Surge Atlas for
Corpus Christi, Texas. NOAA Technical Memorandum NWS NHC 27, National
Hurricane Center, National Weather Service, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, Coral Gables, FL , 438 pp.
Jordan, C.L., 1957: Estimating Central Pressure of Tropical Cyclones from
Aircraft Data, National Hurricane Research Project Report No. 10, Weather
Bureau, U.S. Department of Commerce, West Palm Beach, FL, 12 pp.
Jordan, H.M. and S towel 1, D.J. , 1955: Some Small-scale Features of the Track of
Hurricane lone, Monthly Weather Review , Vol 83, pp. 3 15-326.
Kuo, H.L. , 1959: Dynamics of Convective Vortices and Eye Formation. In The
Atmosphere and Sea in Motion , Rockefeller Institute Press, New York, NY,
pp. 413-424.
Lambeth, B., 1983: Hurricane Alicia: Special Report , Radian Corporation,
Austin, TX, 20 pp. — - — ~
Lawrence, M.B., 1978: Atlantic Hurricane Season of 1911, Monthly Weather Review ,
Vol. 106, pp 534-540. -..— — —-
Lawrence, M.B. and Pelissier, J.M., 1981: Atlantic Hurricane Season of 1980,
Monthly Weather Review , Vol. 109, pp. 1567-1582
Ludlam, W. , 19 63: Early American Hurricanes , 1492-1870, American Meteorological
Society, Boston, MA, 198 pp.
Malkin, W., 1959: Filling and Intensity Changes in Hurricanes Over Land.
National Hurricane Research Project Report No. 34, Weather Bureau,
U.S. Department of Commerce, Washington, DC, 18 pp.
Marks, F.D. , Jr. , 1985: Evolution of the Structure of Precipitation in Hurricane
Allen, Monthly Weather Review , Vol. 113, No. 6, pp. 909-930.
Marshall, R.D., 1984: Fastest-mile Windspeeds in Hurricane Alicia, NBS Technical
Note 1197, National Bureau of Standards, U.S. Department of Commerce,
Washington, DC, 61 pp.
Merceret, F.J., Davis, H.W., DeVivo, R. , Lewis, W.M. Mai linger, W.D. , and
Zysko, A., 1980: In-Flight Calibration of the NOAA/RFC Meteorological Research
Aircraft Instruments at the Air Force Eastern Test Range: 1977-1978, NOAA
Technical Memorandum ERL-RFC-6, Environmental Research Laboratories, National
Oceanic and Atmospheric Administration, U.S. Department of Commerce, Miami, FL,
64 pp.
Merrill, R.T. , 1984: A Comparison of Large and Small Tropical Cyclones, Monthly
Weather Review , Vol. 112, pp. 1408-1418.
Miller, 3.1. , 1958: The Three-Dimensional Wind Structure Around a Tropical
Cyclone, National Hurricane Research Project Report No. 15, Weather Bureau,
U.S. Department of Commerce, Miami, FL.
143
Miller, B.I. , 1963: On the Filling of Tropical Cyclones Over Land, with
Particular Reference to Hurricane Donna of 1960, National Hurricane Research
Project Report No. 66, Weather Bureau, U.S. Department of Commerce, Washington,
DC, 82pp.
Myers, V.A., 1954: Characteristics of United States Hurricanes Pertinent to
Levee Design for Lake Okeechobee, Florida, Hydrometeorological Report No. 32,
Weather Bureau, U.S. Department of Commerce, and Corps of Engineers, U.S.
Department of the Army, Washington, DC, 106 pp.
Myers, V.A., 1975: Storm Tide Frequencies on the South Carolina Coast, NOAA
Technical Report NWS-16, National Weather Service, National Oceanic and
Atmospheric Administration, U.S. Department of Commerce, Silver Spring, MD,
79 pp.
National Academy of Science, 1983: Evaluation of the FEMA Model for Estimating
Potential Coastal Flooding from Hurricanes and Its Application to Lee County,
Florida, Committee on Coastal Flooding From Hurricanes, Advisory Board on the
Built Environment, Commission on Engineering and Technical Systems, National
Research Council, National Academy Press, Washington, DC, 154 pp.
National Hurricane Center, 1980: Hurricane Allen, Climatological Data, National
Summary , National Climatic Center, Environmental Data and Information Services,
National Oceanic and Atmospheric Administration, U.S. Department of Commerce,
Asheville, NC .
National Hurricane Center, 1983: Hurricane Alicia, Climatological Data, National
Summary 1983, National Climatic Data Center, National Environmental Satellite,
Data and Information Service, National Oceanic and Atmospheric Administration,
U.S. Department of Commerce, Asheville, NC.
NOAA Data Buoy Center, 1984: NDBC Observations During Hurricanes Alicia and
Barry, 1983, National Weather Service, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, NSTL, MS, 34 pp.
Neumann, C.J., Cry, G.W. , Caso, E.L., and Jarvinen, B.R. , 1981: Tropical
Cyclones of the North Atlantic Ocean, 1871-1981, National Climatic Center,
National Oceanic and Atmospheric Administration, U.S. Department of Commerce,
Asheville, NC, 17 4 pp.
Palmen, E., 1956: Formation and Development of Tropical Cyclones, Proceedings of
the Tropical Cyclone Symposium , Brisbane, Australia, pp. 212-231.
Palmen, E. and Newton, C, 1969: Atmospheric Circulation Systems, Their
Structure and Physical Interpretation , Academic Press, New York, NY, and
London, pp. 515-522.
PeCterssen, S. , 1956: Weather Analysis and Forecasting . McGraw-Hill Book Co.,
Inc., New York, NY, Vol. 1, 428 pp.
Powell, M.D., 1982: The Transition of the Hurricane Frederic's Boundary-Layer
Wind Field from the Open Gulf of Mexico to Landfall, Monthly Weather Review ,
Vol.110, pp. 1912-1932.
144
Powell, M.D. , Marks, F.D., Jr., and Black, P.G. , 1984, The Asymmetric Structure
of Alicia's Windfield at Landfall, Proceedings, Conference on Coastal
Engineering, Galveston, TX , American Society of Civil Engineers.
Riehl, H. , 1954: Tropical Meteorology , McGraw-Hill Book Company, New York, NY,
392 pp.
Roberts, N.C., Jr., 1969: The Story of Extreme Hurricane Camille, August 14
Through August 22, 1969. Privately published report, Copyright by Nash C.
Roberts, Jr., New Orleans, LA, 135pp.
Saffir, H.S., 1977: Design and Construction Requirements for Hurricane Resistant
Construction, American Society of Civil Engineers, New York, Preprint
Number 2830 , 2 pp.
SAS Institute, 1982: SAS User's Guide: Basics , SAS Institute, Inc., Cary, NC .
Schloemer, R.W. , 1954: Analysis and Synthesis of Hurricane Wind Patterns Over
Lake Okeechobee, Florida, Hydrometeorological Report No. 31, Weather Bureau,
U.S. Department of Commerce, and Corps of Engineers, U.S. Department of the
Army, Washington, DC, 49pp.
Schwerdt, R.W. , Ho, F.P., Watkins, R.R., 1979: Meteorological Criteria for
Standard Project Hurricane and Probable Maximum Hurricane Windfields, Gulf and
East Coasts of the United States, NOAA Technical Report NWS 23, National
Weather Service, National Oceanic and Atmospheric Administration, U.S.
Department of Commerce, Silver Spring, MD, 317 pp.
Shapiro, L.J. , 1977: Tropical Storm Formation from Easterly Waves: A Criterion
for Development, Journal of the Atmospheric Sciences , Vol. 34, pp. 1007-1021.
Shea, D.J. and Gray, W.M. , 1972: The Structure and Dynamics of the Hurricane's
Inner Core Region, Atmospheric Science Paper No. 182, NOAA Grant N22-65-72 (G) ,
NSF Grant GA 1993 7, Department of Atmospheric Science, Colorado State
University, Fort Collins, CO, 134 pp.
Sheets, R.C., 1977: On the Evolution of Hurricane Anita, Presented at the
Eleventh Technical Conference on Hurricanes and Tropical Meteorology, Miami
Beach, FL pp. 495-465.
Simpson, R.H. , Sugg, A.L. , and Staff, 1970: Atlantic Hurricane Season of 1969,
Monthly Weather Review , Vol. 98, pp. 295-300.
Sugg, A.L. , Pardue, L.G. , and Carrodus, R.L., 1971: Memorable Hurricanes of the
United States Since 1873, NOAA Technical Memorandum NWS SR-56, National Weather
Service, National Oceanic and Atmospheric Administration, U.S. Department of
Commerce, Fort Worth, TX, 52 pp.
Taylor, G. and Staff, 1981: Annual Data and Verification Tabulation, Atlantic
Tropical Cyclones - 1980, NOAA Technical Memorandum NWS NHC 15, National
Hurricane Center, National Weather Service, National Oceanic and Atmospheric
Administration, U.S. Department of Commerce, Miami, FL, 78 pp.
145
U.S. Army Corps of Engineers, 1983: Hurricane Alicia, 15-18 August 1983 , Army-
Engineer District, Galveston, TX, 44 pp.
Weather Bureau, 1968: Interim Report — Meteorological Characteristics of the
Probable Maximum Hurricane, Atlantic and Gulf Coasts of the United States,
unpublished memorandum HUR 7-97, U.S. Department of Commerce, Silver
Spring, MD, 45 pp.
Weatherford, C.L. , 1985: Typhoon Structure Variability. Department of
Atmospheric Science Paper No. 391, Colorado State University, Ft. Collins, CO,
77 pp.
Willoughby, H.E., 1979: Some Aspects of the Dynamics in Hurricane Anita of 1977,
NOAA Technical Memorandum ERL-NHEML-5, Environmental Research Laboratories,
National Oceanic and Atmospheric Administration, U.S. Department of Commerce,
Miami, FL , 30pp.
Willoughby, H.E., Clos, J. A., and Shoreibah, M.G. , 1982: Concentric Eye Walls,
Secondary Wind Maxima, and the Evolution of the Hurricane Vortex, Journal of
the Atmospheric Sciences , Vol. 39, pp. 395-411.
Willoughby, H.E., 1985: Confirmatory Observations of Concentric Eyes in
Hurricanes, Extended Abstracts, 16th Conference on Hurricanes and Tropical
Meteorology, American Meteorological Society, Boston, MA.
146
APPENDIX A
Detailed Analysis of Selected Storms
A.l Introduction
Data for storms that have occurred since TR 15 and are included in Tables 1 to
3 were based on consideration of research work done by others and our own
detailed analyses. This Appendix provides examples of the analyses leading to
development of the parameters used in this study. The first storm discussed is
Hurricane Alicia, which is representative of Gulf storms. We then discuss
Hurricane David which affected the Atlantic coast. David was also used in
Chapter 4 to examine the relation between P and R. Finally, we conclude with an
examination of Hurricane Allen. Allen was used in Chapter 4, and is an example
of an intense storm undergoing a number of strengthening and weakening cycles.
A.2 Hurricane Alicia, August 15-21, 1983
A-2 .1 Introduction
Hurricane Alicia was the first hurricane since Carla (1961) to cause extensive
damage in the Houston-Galveston, Texas area (estimated at 1.8 billion [1983]
dollars). By hurricane standards, Alicia was only a medium sized hurricane that
reached a minimal category 3 status (based upon the Saf fir/Simpson scale) at
landfall. Carla was a much larger and more intense hurricane than Alicia, but
Alicia struck a highly urbanized coastal area. Alicia caused more damage than
Carla - the estimated total damage of nearly 2 billion dollars is the largest
dollar damage ever recorded for a hurricane striking Texas. If a hurricane the
size and strength of Carla were to strike close to the Galveston Bay area today,
the losses have been estimated to be two to three times more than those caused by
Alicia (Case and Gerrish 1984).
While the analyses described in this Appendix can provide useful information on
a single storm event for calibration of hurricane surge computation using a
numerical model, the purpose of the analyses was to specify clima tological
hurricane parameters. These are central pressure, speed and direction of forward
motion, and the radius of maximum winds.
A.2 .2 Previous Reports
The National Hurricane Center provided a description of significant features of
all Atlantic tropical storms that occurred during 1983, including Hurricane
Alicia, in the Monthly Weather Review (Case and Gerrish 1984) and in the National
Summary of Climatic Data (National Hurricane Center 1983). These publications
also included a smoothed "best" track for Alicia. The NHC publication on annual
data and verification tabulation for the 1983 Atlantic tropical cyclones (Clark
and Staff 1984) also includes a list of Alicia's center-fix positions obtained
by aerial reconnaissance penetrations, satellite images, and land-based radar.
The hurricane's central pressure, maximum winds and other data observed by
reconnaissance aircraft are also included in that report. Meteorological data
collected at data buoy stations in the Gulf of Mexico can be found in the report
"NDBC Observations During Hurricanes Alicia and Barry, 1983," published by the
NOAA Data Buoy Center (1984).
147
Lambeth (1983) provided a summary of available information about Hurricane
Alicia. It included maximum wind, minimum pressure, and times of occurrences of
both, reported from regular reporting stations and other sources, including the
Texas Air Control Board (6 stations), Houston Regional Monitoring Corporation
(12 monitoring stations) in the Houston-Galveston area, and the Dow Chemical
Plant in Freeport, Texas.
Marshall (1984) used surface windspeeds recorded during the passage of Alicia
to estimate fastest-mile windspeeds at 10 m above ground and compared these
speeds with recommended windspeed criteria for the design of buildings and other
permanent structures. Powell et al. (1984) described the asymmetric character of
the windfield in Hurricane Alicia and the changes in the winds during landfall.
They found that the strongest surface and flight-level winds showed a close
relationship to the precipitation structure of the storm as depicted by radar.
Willoughby (1985) also described the evolution of Alicia's windfield as the
hurricane made landfall.
The Galveston District of the U.S. Army Corps of Engineers (1983) evaluated
storm damage caused by Alicia and published summaries of hydrologic, meteorologic
and damage data. Garcia and Flor (1984) compiled coastal and inland tide gage
data and high-water marks associated with Hurricane Alicia. They also included
wave data and wave spectra in their report.
A .2 .3 Sources of Data
The reports discussed in the previous section were used to the maximum extent
possible in the present study. We also examined original records to ensure the
accuracy and completeness of this study and to enable us to provide more detailed
information on track position, speed, central pressure, etc. This permitted us
to perform the most comprehensive and detailed analysis yet developed for
meteorological factors associated with Alicia and important to storm-surge
modeling.
The basic information was obtained from the regularly reporting network of
weather stations operated by NWS, NOAA and the military services. These reports
are maintained at the National Climatic Data Center in Asheville, North Carolina.
Supplemental data, available in the NCDC archives, included ship observations,
radar observations, radiosonde records, reconnaissance flight data and satellite
observations.
In addition, meteorological data collected by research aircraft of NOAA' s
Office of Aircraft Operations (0A0) were processed by computer and stored on
magnetic tapes at the Hurricane Research Division (HRD) of NOAA's Atlantic
Oceanographic and Meteorological Laboratory (AOML) in Miami, Florida. This
information was made available to us for this report. A detailed description of
the collection of meteorological information by aircraft, including the
instrumentation, its calibration, and reliabilities, has been included in
Hawkins et al. (1962). A more recent discussion of the calibration and
instrumentation of present-day NOAA research aircraft can be found in other
publications (e.g., Merceret et al. 1980). Availability of airborne research
meteorological data collected by HRD/AOML are included in Friedman et al. (1982,
1984).
148
A.2 .4 General Meteorological Situation
The system which developed into Hurricane Alicia on August 17, 1983, initially
formed in the northern portion of the central Gulf of Mexico. This system
intensified into a tropical storm around mid-day of August 15 and drifted
westward for the next 2 4 hours.' Surface pressures were high over the Gulf of
Mexico and remained high during the early stages of the storm's development.
Several ships located near the storm reported pressures of 1015 to 1016 mb late
on the 15th. During this time the storm remained quite small and generated winds
stronger than usually observed in storms with similar minimum central
pressures. Alicia turned toward the west-northwest on the afternoon of August 16
and attained hurricane intensity on the morning of the 17th. Hurricane Alicia
moved northwestward at the a steady pace and crossed the Texas coast about 30 nmi
southwest of Galveston at 0700 GMT on August 18. The minimum pressure at the time
of landfall was 962 mb. Maximum sustained winds of 78 kn were reported by a
Coast Guard Cutter near Galveston. Alicia maintained its hurricane intensity for
the 6 hours after making landfall. Maximum winds of 77 kn were reported at 1050
and 1524 GMT at Pearland, Texas, and 70 kn at 1300 GMT at Baytown, Texas. After
passing the southwestern suburbs of Houston, Texas, Alicia weakened rapidly and
moved northwestward over Texas and then northward over western Oklahoma.
A.2 .5 Detailed Meteorological Analysis
A primary focus of this study was to analyze in detail hurricane parameters
used in storm-surge models in order to develop a statistical climatology. For
this purpose, we analyzed raw observational data. The intent of these analyses
was to develop specific values of the hurricane's central pressure, radius of
maximum winds, direction and speed of forward motion, and location of its center
at various time intervals. Particular attention was focused on the period just
before and after the hurricane made landfall since this is the time interval most
critical for storm-surge computation.
A.2 .5.1 Storm Track, Generally, the analyses of meteorological data are
weighted toward synoptic-scale motion. The hurricane track, thus obtained, is
the best estimate of the large-scale motion and not necessarily the most precise
location of the eye at discrete time intervals. Track differences of a few
miles, insignificant in determining the large-scale motion, can be significant
for replicating high water on the open coast and inside bays and estuaries in
surge-model computations.
Figure A.l shows the final track determined for Hurricane Alicia from 0000 CST
(0600 GMT) on August 16 through 1200 CST (1800 GMT) August 18 together with
locations of meteorological stations used in this report. Except for Baytown,
the stations are either NWS offices or military installations reporting regularly
to the NWS. The positions of the storm center are shown at 6-hour intervals.
The central pressure (mb) and the radius of maximum winds (nmi) are plotted to
the left of 12-hour positions. Direction of storm motion at landfall was
determined from figures such as this.
Any final determination of the track and speed of forward motion of a
hurricane, especially over data-sparse regions, has inherent uncertainties. The
track that was finally chosen was based on subjective analysis of all available
information. Figure A.2 is an example of the information used in our analysis.
149
990 4
30
kl200
96*
\ 1AH . 9Z .
\ HOUSTON 9_5' M« ^ +3tf
\ BAYTOWN^Uj ^^___ -^^ 'v*'^^ £" J
» ELLINGTON AFB--->u-,^-^ U L F ' ^~Jr
\0600 "S w r J^^ Op >-*
\ # "^\ >^^ MEXICO
\ /^^GALVESTON
+
FRECPORT J^""^ +■
4- +29'
-^ 964(»0000CST/I8t» Aw,.
^S 30 j
LEGENO
990 CENTRAL PRESSURE (mb)
35 RAORJS OF MAX. WNOS <nmi)
0000 TIME (CST)
\i800
+
974*1200
, 14 / I -L +23*
( 0600
987$OOOOCST/l 7tn Ay,.
24 \
\^__I800
"""^»>~ 1200
998^*^
20 >«.
^^0600
+
. , -f. ^"soooocsi/ieto
95' 94* 93* !< JP| S, 9'
96"
Figure A-l. — Hurricane track for Alicia, 0000 CST August 16 through 1200 CST
August 18, 1983.
Hurricane eye positions based on radar observations reported from Galveston,
Texas, and Lake Charles, Louisiana, are shown as solid dots. Aircraft
reconnaissance penetration fixes are shown by triangles. Locations of the
hurricane's center determined from satellite observations are given by
diamonds. The data from radar fixes and aircraft penetrations were the primary
sources used in determining the track and speed of the hurricane over the open
ocean. However, information obtained from satellite observations and from ships
and oil rigs operating in the area was considered in determining the final track
and speed of motion.
A.2.5.2 Forward Speed. The translation speed of the hurricane is an important
factor in determination of the surge along the open coast and in bays and
estuaries. Hourly positions were the basic data used to determine the forward
speed. Speeds between successive hours from positions along the best track were
first determined and plotted on a time scale and smoothed. Then smooth curves
drawn from these data were used to adjust the hourly locations. The new
locations were examined with regard to the observed data and, if necessary, some
further adjustments were made. This process was continued in an iterative
fashion until the best combination between smooth forward speeds and observed eye
150
<•> £f
28°N +
95 °W
• • •*•
Q
LAKE CHARLES
• • •
Figure A. 2. — Hurricane eye position obtained froa radar (•), aircraft
reconnaissance penetration fixes (A), and satellite observations (<i>).
151
Figure A.3 • — Minimus pressure recorded at land stations and by
reconnaissance during Hurricane Alicia (1800 CST August 16 -
August 18, 1983).
aircraft
1200 CST
positions was obtained. This process helped to obtain the best possible estimate
of forward speed and hourly locations.
A.2.5.3 Central Pressure. The most important meteorological input to storm-
surge models is the intensity of the hurricane which can be parameterized in
terms of its central pressure. Minimum pressures observed at stations and during
reconnaissance aircraft penetrations are presented in Figure A.3. These
observations were not all obtained at the same time. Since the track of the eye
did not cross any land station location, none of the values reported at land
stations are equal Co the 'minimum central pressure in the storm.
Figure A. 4 shows our analysis of pressure data from land stations and aircraft
reconnaissance flights used to obtain a cime history of Alicia's central
pressure. A smooth curve was fit to the data by eye. Alicia deepened gradually
152
o
o
O
o
en
03
o
05
05
<W 3dflSS3dd !VyiN30
153
at an average rate of 1 mb per hour starting from 1200 GMT on August 16 until it
reached a minimum value almost 2 hours after landfall. A reconnaissance aircraft
recorded the minimum pressure of 962 mb at 0842 GMT on August 18 (fig. A. 4). We
consider this pressure to be the lowest that occurred in Hurricane Alicia. The
short time intervals between central pressures obtained by aircraft, combined
with other information (cited in sec. A.2.2), did not indicate any lower pressure
at intermediate times.
As Alicia continued its north-northwesterly course overland, its intensity
weakened only gradually over the next several hours. Alicia's central pressure
reached its minimum and stayed nearly unchanged for another 2 to 3 hours after
the hurricane center crossed the coast. Hurricane central pressure usually rises
rapidly after the storm center moves over land. The central pressure of
Camille (1969), which was a small and intense hurricane, rose at a rate of about
10 mb per hour for about 5 hours after its center crossed the Mississippi
coast. For Alicia, the lowest sea-level pressure recorded at Alvin, Texas, was
967 mb and at Pearland, Texas, it was 972 mb. Alicia weakened rapidly soon after
it passed the southwestern suburb of Houston, Texas. Its central pressure
rose to 980 mb as its center passed near Spring, Texas, just 14 nmi west by north
of Houston Intercontinental Airport (sea-level pressure at Spring reached 982 mb
at 0952 CST or 1552 GMT - see fig. A.3).
A.2.5.4 Wind Analysis. In addition to the minimum pressure reported at stations
during hurricane passage, surface winds were recorded at several weather stations
operated by the NWS and the military services. The Hurricane Landfall Program
executed by the HRD of the AOML, NOAA, recorded radar data and collected post-
storm surface meteorological data from numerous NWS and private sources
(Powell et al. 1984). This data collection was made available to us for this
study. We analyzed the windfield for Alicia in two ways. We first examined the
wind observations of land stations. Next, we did composite streamline analyses
of the windfields at various intervals near the time of landfall. This wind
analysis was used to aid in the determination of the radius of maximum winds. It
also provided some guidance in determining the best track.
Figure A. 5 shows the time variation of windspeed and sea-level pressure
recorded at Houston Intercontinental Airport, Texas. The figure shows that the
maximum wind of 51 kn occurred some 3 hours before the minimum pressure was
reached at about 1450 GMT on August 18. The maximum wind was observed when the
hurricane center was about 28 nmi (51.8 km) south of the station. Figure A. 6
shows similar curves for pressure and windspeed recorded at the EXXON office in
Baytown, Texas. A maximum wind of 70 kn was observed at 1300 GMT when the storm
center was 31 nmi (57.4 km) to the west.
Since surface data were too limited and scattered to analyze the winds when the
hurricane was located some distance off the coast, all reconnaissance aircraft
observations within intervals of several hours were combined and plotted. This
technique, called composite analysis, makes use of the hurricane center as the
basis of the coordinate system. The position of each observation taken in aerial
reconnaissance was measured in terms of azimuth angle and radial distance
relative to the hurricane center at the time of observation. Each wind
observation was then transposed to the relative location with respect to the
hurricane center at map time. Figure A. 7 shows a composite analysis based on the
flight-level wind observations taken from 2040 GMT on the 17th through 0040 GMT
on the 18th. The transposed observations are shown in this chart. The figure
154
60
I I 1
HURRICANE ALICIA J 983
PRESSURE
PRESSURE AND WIND SPEED
RECORDED AT HOUSTON (IAH),TX
06
i/00
06
020
000
<
98o a
970
! 2
18
9/00
06
TIME (GMT)
Figure A.5. — Hourly observations of sea-level pressure and surface wind speed
recorded at Houston Intercontinental Airport, Texas, (0600 GMT August 17 -
0600 GMT August 19, 1983).
shows an isocach (isolines of constant windspeed) analysis of flight-level
(1,500 m or 5,000 ft) winds* The isolines are labeled in kn. The analysis is
assumed to apply to Che center time (2240 GMT) of the composite period. Maximum
winds of about 85 kn were observed in the front semi-circle at about 15 nmi (2 7.3
km) from the storm center.
Powell et aim (1984) constructed composite maps using mean surface and flight-
level wind data, adjusted to the 10-m level. The observations were plotted at
transposed locations, relative to the wind center of the storm, as determined
from aircraft reconnaissance fixes, surface winds, sea-level pressures and radar
data. Figure A. 8 shows the streamline and isotach analysis of a composite map
from Powell et al., near the time of landfall (0730 GMT). The analysis assumed
that the storm structure and intensity had not changed during the period of
composite, 0400-1100 GMT on August 18. At this time, Alicia exhibited a double
eye structure. The maximum winds observed during this period in the storm
(3 9 m/sec or 78 kn) were found in the outer radius by a Coast Guard cutter near
Galveston, Texas. The extreme winds near the inner core (ayewall) were slightly
less than those of the outer maximum which was about 30 nmi (55.6 km) from the
storm center. Analysis of flight-level winds for the same oeriod (diagram not
shown) revealed maximum flight-level winds of 90-100 kn occurring at about 30 nmi
155
50 -
Q
UJ
UJ
Q.
W 30
Q
Z
20-
10
- 1020
1010
HURRICANE ALICIA J 983
PRESSURE AND WIND RECORDED
AT BAYTOWN (EXXCN) t TX
I I I I
x
ooo 55
CO
UJ
cc
a
990 g
<
co
980
— 970
06 12 18 13/00 06 12 13 19/00 06
TIME (GMT)
Figure A. 6. — Same as Figure A.5 for Baytown, Texas.
(55.6 km) to the right of the storm center. This agrees very well with surface
wind observations. A secondary wind maximum (80-85 kn) , nearer the eye at
flight-level, was located in the right rear quadrant of the storm.
A.2.5.5 Radius of Maximum Winds. A common measure of hurricane size is the
distance between the storm center and the band of highest winds. The determina-
tion of the radius of the maximum winds was made on the basis of all available
data for this storm. Three different types of observations were used. The first
included maximum flight-level winds and estimated surface winds as reported by
reconnaissance aircraft. The second was the radar-estimated eye wall diameter,
as well as data on the size of the eye as reported by reconnaissance aircraft and
by surface stations. Some visual reports were used when the reconnaissance
aircraft were in the eye of the storm. The third measure, useful only after the
hurricane was near shore, was the estimated radius deduced from wind records at
land stations. In Alicia, we relied heavily on the first and the third measures
to determine the R value.
Figure A. 9 shows flight-level winds recorded at the 850-mb level between
13 52-1433 GMT on August 17. The winds were recorded at 1-second intervals by
reconnaissance aircraft of MOAA's Office of Aircraft Operations and were
processed and plotted as a function of radial distance from the hurricane
center. The winds obtained during a traverse of the eye along a path 349° to
169° revealed that maximum winds of about 45 m/sec (90 kn) occurred near 30 km
156
.57
30°N
29°N
28°N
96°W
95°W
94°W
Figure A. 3. — Streamline (solid lines) and 10-m isotach (dashed lines) analysis
for Hurricane Alicia, 0730 OCT August 18, 1983 (from Powell et al. 1984).
(16 nmi) from the storm's center. Similar radial wind profiles constructed from
winds recorded in each traverse of the hurricane eye were plotted bv computer and
made available to us by the HRD/AOML, NOAA. Examining a series of wind profiles,
we obtained estimates of R at various times. Further analysis of composite
charts of flight-level winds, previously discussed, provided additional insight
into the time history of R in Alicia.
Figure A. 10 shows the radial distance of wind maxima, thus obtained, at various
times between 0600 GMT on August 17 and 0000 GMT on the 19th. Smooth lines drawn
through these data points provided us with curves from which the radius of
maximum winds was determined. Radial distances of maximum winds obtained from
analysis of flight-level winds are shown by solid boxes; those deduced from
surface winds recorded at land stations are given by triangles. The magnitude of
extreme winds recorded at a given time was classified into two categories, a
primary and a secondary wind maximum. The primary wind maximum is denoted by a
solid line, while the secondary wind maximum is indicated by a dashed line. A
shift of the primary wind maximum from a radial distance of about 15 nmi
(2 7.8 km) to about 30 nmi (55.6 km) from the center seems to have occurred around
0600 GMT on August 18.
158
Nl u >
/-j
M/'-
90
30
50 30 10 -10 -30
STORM DISTANCE (km)
Figure A.. 9. — Flight-level (1500 a) vind3 recorded along radials through the
center of Hurricane Alicia, 1352-1433 GMT August 17, 1983.
A«2 .6 Discussion
The value of R is one of the important factors Co be prescribed in a numerical
computation of hurricane surges at the coast as well as in bays and estuaries.
The R value, together with a precisely determined storm track specify the
location of maximum winds along the coast. This, in turn, influences the water
level produced by surface wind stress in a storm-surge model. It is important
for surge modelers, as well as users of hurricane surge models, to have precise
meteorological information in order to calibrate or verify a numerical surge
model. The radius of maximum winds for Alicia shifted from 15 nmi (2 7.8 km) to
3 nmi (58.6 km) near the time of landfall. The transformation of storm size for
Alicia took several hours to complete. The high winds near the inner core caused
severe damages to downtown Houston, Texas. However, high-water levels in
Galveston 3ay (close to 11 ft above MSL at Baytown, Texas) were generated by the
winds within the region of highest winds. After examining all available data, we
concluded that R for Alicia shifted from 15 nmi (27.8 km) to 30 nmi (55.6 km)
just before the hurricane made landfall and that the larger R should be applied
to surge computations for the Galveston Bay area.
Hurricane data of recent years have shown large variabilities in hurricane
parameters at various stages of a hurricane's life cycle. After a hurricane
moves over land, its characteristics often change abruptly, due to larger surface
friction and modifications to the heat and energy supply. Such changes in the
characteristics of the hurricane would result in a departure from the
standardized wind profile of the storm-surge model. Hurricane parameters,
especially the index R, given in Tables 1 through 3 may not be the best values
159
2
X 40
O
1 1 1
RADIAL DISTANCE OF WIND MAXIMA
HURRICANE ALICIA, AUGUST I 983
- RECON. DATA
7 LAND STATIONS
TIME (GMT)
Figure A. 10. — Radius of primary (solid line) and secondary (dashed line) wind
maxima in Hurricane Alicia, August 17-18, 1983.
for replicating observed surges with a standardized wind profile. The variation
in R near landfall might have to be examined on a case-by-case basis before a
suitable value can be determined for the calibration of a numerical surge
model. In the calibration process, the computed model winds, in addition to the
computed high-water level, should be verified using observed data to ensure the
adequacy of the wind model used in the numerical surge computation.
A.3 Hurricane David, September 2-5, 1979
A.3.1 Introduction
Hurricane David emerged from the central Caribbean on September 2 after
devastating the Dominican Republic and rapidly weakening to tropical storm
strength over the mountains of Hispanola. David was the strongest hurricane to
hit Santo Domingo, Dominican Republic since 1930 (Hebert 1980). Once over water
north of Cuba, David began to reintensify as it moved northwestward and
approached Andros Island in the western Bahamas with winds of 61-69 kn
(DeAngelis 1979). As the center crossed the island late in the afternoon on
September 2, it appeared to be heading toward the Miami area (fig. A. 11). A turn
to the north-northwest, however, brought the slowly strengthening hurricane about
50 nrai (92.6 km) east of Miami on Labor Day, September 3. Winds of 50 kn were
reported buffeting Miami 3each by 0800 GMT September 3. David continued moving
north-northwestward and passed within 2 5 nmi (46.3) of West Palm 3each with a
minimum central pressure of 973 mb at 1445 GMT September 3. Winds of 50 kn were
experienced at West Palm Beach shortly before David's nearest approach. At
1730 GMT on September 3, the storm center made landfall just south of
Stuart, Florida, with a central pressure of 968 mb. Winds of 60 kn were recorded
160
Figure A.ll. — Track with central pressures (mb) for Hurricane David,
September 2-5, 1979.
161
Table A.l. — Time, flight pattern, and flight level of NOAA/RFC missions into
Hurricane David, September 1979
Mission
Time period
(GMT)
Pattern
Flight level(s)
(ft)
790902F
7909021
7 90902H
02/0145-092 5
02/1130-1853
02/2002-03/0454
east-west
race track
star
Recon.
5,000
variable
variable
790903F
7909031
03/0504-1240 star (see fig. A. 12) 5,000
03/2312-04/0641 along FL coast variable
790904H
04/1723-05/0128
modified star
(eye partly onshore)
variable
The missions are designated by an identification code, YYMODAAC where:
YY = year (F = NOAA/RFC C130B aircraft 41
MO = month AC = aircraft (H = NOAA/RFC WP-3D aircraft 42
DA = day of the month (i = NOAA/RFC WP-3D aircraft 43
at Stuart at 1600 GMT. David remained close to the Florida east coast for the
next 11 hours as it moved north-northwestward over land. By 0600 GMT
September 4, the storm center had moved back over open water north of Cape
Canaveral. David was the first hurricane to strike the Cape Canaveral area since
192 6 (Hebert 1980). Central pressures in David remained steady as it made its
way north toward Georgia. Landfall occurred for a second time in the United
States at 1822 GMT September 4 north of Brunswick, Georgia, with a minimum
central pressure of 968 mb. David continued on a northerly track and passed just
west of Savannah, Georgia, at 2346 GMT September 4.
A .3 .2 Previous Studies
Hebert (1980) prepared a detailed description of Hurricane David and included
meteorological data from land stations as far south as the Lesser Antilles, and
as far north as Mt. Washington, New Hampshire. He compiled meteorological data
from regularly reporting stations, as well as various unofficial sources which
were used in the analysis of the variation of central pressure with time (shown
in fig. A. 15). The National Hurricane Center published an annual verification and
data tabulation for Atlantic tropical cyclones of 1979 which included Hurricane
David (Hebert and Staff 1980). The compiled data tabulations give David's
center-fix positions obtained by aerial reconnaissance penetrations, satellite
images, and land-based radar. Central pressures, maximum winds and other data
observed by aerial reconnaissance were also included for Hurricane David.
162
DIRECTION OF STORM MOVEMENT
Optiona
80 NM leg
Figure A. 12. — Reconnaissance flight pattern, designated as star pattern,
Hurricanes David and Allen (refer to Friedman et al. 1982).
used in
Howell at al. (1982) provided a report of tide data during; the passage of
Hurricane David at Miami Beach, Palm Beach, and Vero Beach, Florida. Storm
surges at Palm Beach and Vero Beach were computed by Howell et al. using a
numerical storm-surge model and compared with observed values.
A.3.3 Aircraft Data
NOAA research aircraft flew six missions into Hurricane David during the period
September 2-5. Table A.l summarizes the flight patterns, flight levels and the
time periods for which meteorological and flight data were recorded. The flight
patterns flown in these missions included a 'star' type (fig. A. 12) and a 'Recon'
type. The 'Racon' flight pattern was a deviation from typical flight patterns.
In this case, the actual pattern completed was designed to optimize both the
determination of the storm center location and collection of research data. A
163
detailed inventory of airborne research meteorological data is described by
Friedman et al. (1982). This set of NOAA flight data was supplemented by Air
Force reconnaissance flight data recorded on the morning of September 4.
A.3 .4 Central Pressure
A.3 .4.1 P From Aerial Reconnaissance. Minimum central pressures were recorded
nearly continuously from September 2-4 by NOAA and Air Force reconnaissance air-
craft when Hurricane David was moving over open water. Pressure values were
obtained from Hebert et al. (1980). These pressure values were used in
Figure A. 15. When Hurricane David moved over land, reconnaissance aircraft did
not penetrate the eye to obtain a pressure reading because of increased
turbulence over land.
A.3 .4.2 P Q From Land Station Observations. Once Hurricane David was over land,
station reports of hourly weather observations and barograph traces were used to
determine minimum pressures. If the center of the hurricane eye passed directly
over a land station, then the minimum pressure could be readily determined.
Hurricane David, however, did not pass directly over any land stations. Since
several stations were very close to the track, their minimum pressures were used
to estimate the storm's minimum pressure. Figure A. 13a shows the time variation
of minimum pressures recorded at Shuttle Airport, Florida every 3 hours. From
this plot, the lowest pressure observed during the passage of David, 974 mb,
occurred at about 0300 GMT September 4, when the storm's eye was located only
about 5 nmi (9.3 km) to the west of the station. This estimate was plotted in
Figure A. 15. Another example of (hourly) station pressure data is shown in
Figure A. 13b for Savannah Municipal Airport, Georgia. A minimum pressure of
970 mb was experienced at 2300 GMT September 4 when David was about 7 nmi (13 km)
to the west. This estimate was also used in the analysis shown in Figure A. 15.
A.3 .4.3 Pressure Fit at the Coast. Minimum pressures determined at the Florida
and Georgia coasts were not based on any single source. Observed pressures were
extrapolated inward to P using visually-fitted radial pressure profiles based on
equation 1. Figure A. 14a shows a subjectively fit pressure profile curve at the
Florida coast, near the time of landfall, at 2100 GMT September 3. Pressure
observations from several land stations were plotted against distance from storm
center at 2100 GMT. Then a curve was drawn to fit the data. Figure A. 14b is
another example of the pressure profile curve except at 1800 GMT September 4, at
the Georgia coast. In both cases, a minimum central pressure of 968 mb was
estimated. In the case of the Georgia coast, a NOAA research aircraft measured a
minimum 700 mb height of 2 82 m at 1822 GMT September 4. Using a nomogram for
estimating surface pressure in the eye of tropical cyclones (Jordan 1957), a
central pressure of 968 mb was also estimated.
A.3 .4.4 Time Variation of P . Hurricane David was most intense (central
pressure of 92 4 mb) while still located in the Caribbean Sea, south of Puerto
Rico. The analysis for this period was used in Chapter 4. As David emerged from
the central Caribbean Sea, however, central pressures moderated considerably (see
fig. A.ll). Figure A. 15 shows the time variation of central pressure in David
for the period of September 3-5. Minimum pressures recorded by reconnaissance
aircraft and land stations at various times were used to obtain a time history of
David's central pressure. The line drawn is a curve fit to the data by eye.
164
1020
1010
—
1 1 T 1 1
! r ...... , j
^
-3
£
bJ
1000
K
ZD
00
oO
111
a.
990
\ / ~
-j
uj
>
LU
-J
980
\ /
<
LU
CO
970
(a)
-
96C
1., , ! . 1 -L— L_
L 1 1 1
3/00 06
4/00 06
TIME (GMT)
020
1
1 1 1 I !
1 1 r- i
010
-
000
Nl j*
990
-
\ /
980
X i
970
-i
(b)
1 I II
06
4/00
06
5/00
TIME (GMT)
Figure A. 13. — Sea-level pressure observed during passage of hurricane David
(September 1979) at (a) Shuttle Airport, Florida, and (b) Savannah (Municipal
Airport) , Georgia.
165
250 300 350
DISTANCE FROM STORM CENTER C rani)
100 150 200 250 300 350 400
DISTANCE FROM STORM CENTER Cnmi)
Figure A. 14. — Pressure—profile curve during Hurricane David for (a) Florida coast
at 2100 GMT, September 3, 1979, (b) Georgia coast at 1800 GMT, September 4,
1979.
166
o —
©
311IAN0SX0Vr
<?
•WQV38 fl"!Vd '«
■si soaaNv
CO /-» -j
O h- >
2 J
cw 3^nss3dd
167
168
STORM DISTANCE (km)
Figure A.16. — Flight-level ri?As recorded along radlals through the center of
Hurricane David, (a) 2308-2356 QfT, September 2 , (b) 0644-0748 GHT,
September 3, and (c) 1751-1341 GMT, September 4, 1979.
Reconnaissance aircraft reported a minimum pressure of 96 5 mb at 0051 GMT
September 3 just as David crossed Andros Island, about 120 nmi (222 km) southeast
of Miami, Florida. A central pressure of 966 mb was recorded by aerial
reconnaissance at 0302 GMT. By 0531 GMT September 3, another mission reported a
central pressure of 981 mb. The pressure difference in these 2 .5 hours was
15 mb. This large pressure rise seems to be inconsistent with Che other data as
Figure A. 15 shows and no explanation can be given. Hurricane David approached
the southeast coast of Florida at a speed of about 10 kn, and a central pressure
of 968 mb was determined at landfall at about 1730 GMT September 3. This value
is the pressure recorded in Table 2. As David moved northwestward over land
along the Florida coast (fig. A.ll), central pressures increased very gradually
until the storm exited the coast and moved over water again. A central pressure
of 975 mb was consistently reported by Air Force reconnaissance aircraft from
1142-1515 GMT September 4. During this time, David was moving over water north
of Cape Canaveral at about 12 kn. As the hurricane approached the Georgia coast,
pressures dropped at about 2 mb/hr from 1515 GMT until a low pressure of 968 mb
was determined at landfall (see sec. A.3.4.3), about 1822 GMT September 4. David
moved inland at about 10 kn and weakened slowly. Savannah, Georgia experienced a
minimum pressure of 970 mb when the center of David was only about 7 nmi (13 km)
to the west and 40 nmi (74 km) inland.
169
A*3 .5 Radius of Maximum Winds
A.3.5.1 R From Aerial Reconnaissance. Figure A. 16a shows a wind profile
constructed from flight-level wind data recorded between 2 308-2 3 56 GMT
September 2. The winds were recorded during a north-south traverse through the
eye and are plotted against radial distance from the storm center. The figure
indicates that a wind maximum is located to the north of the center at a radial
distance of about 35 km (18.9 nmi). This value was plotted in Figure A. 18 at
2332 GMT September 2. Figure A. 16b is another wind profile for Hurricane David
constructed from flight-level winds recorded between 0644-0748 GMT September 3 .
At this time, the storm center was located over open water about 68 nmi (12 6 km)
east-southeast of Miami, Florida (see fig. A.ll). Flight-level winds were
recorded during a northeast-southwest traverse through the eye. The wind profile
indicates that maximum winds occurred at a radial distance of about 45 km
(24 nmi) northeast of center. This value was plotted in Figure A. 18 at 0716 GMT
September 3. Figure A. 16c shows another wind profile constructed from data
recorded between 1750-1841 GMT September 4. At this time, the storm center was
over water north of Cape Canaveral and approaching landfall on the Georgia
coast. The winds were recorded during an east-west traverse through David's
eye. Figure A. 16c indicates a maximum wind at a radial distance of about 20 km
(10.8 nmi) west of center. This value is plotted at about 1815 GMT September 4
in Figure A. 18. Figures A. 16a through A. 16c suggest the existence of secondary
maxima (indicated by solid dots in fig. A. 18) which were relatively short-
lived. Analysis of composite maps (diagrams not shown) revealed that these
secondary maxima were scattered and quite disorganized. They were not considered
relevant in the specification of the parameters that are the focus of this study.
A.3.5.2 R From Land Station Observations. Once the storm moved inland, land
stations were the primary source of data. Data from these stations were obtained
from the NCDC in Asheville, North Carolina, where all raw data from station
observations are stored.
Figure A. 17a shows a time variation of windspeed and wind direction for Shuttle
Airport, Florida from 1200 GMT September 2, to 0000 GMT September 5. This plot
consists of hourly wind observations as Hurricane David passed just west of the
station (0300-0400 GMT September 4). Note the shift in wind direction as the
storm center passed. Winds veered from the east to east-southeast then south
indicating the path of the storm center was to the west of the station. A
maximum wind of about 3 7-3 8 kn (19-2 m/s) was experienced at Shuttle Airport at
053 GMT September 4 when the storm center was located approximately 2 nmi
(3 7 km) away from Shuttle Airport (see hurricane track on Fig. A.ll).
Figure A. 17a also shows the distance of the storm from Shuttle Airport (dashed
line). Using this information, a radial distance of 2 nmi (3 7 km) was
determined for the wind maxima and was plotted in Figure A. 18 at 0530 GMT
September 4. Figure A. 17b shows another plot of hourly windspeed and direction
against time for Savannah Municipal Airport, Georgia from 0600 GMT September 3 to
1700 GMT September 5. The wind direction at Savannah as David's center passed
nearby shifted from the east to east-southeast then south and finally
south-southwest. This indicates that the hurricane passed to the west of the
station (fig. A.ll). A maximum wind of about 37 kn (19 m/s) occurred at Savannah
at 2230 GMT September 4. The track in figure A.ll indicates that the hurricane
center was only about 10 nmi (18.5 km) away from Savannah at 2230 GMT
September 4.
170
©-^
t
0--
-o~
-0-
^0~-
t
!
--ex®"
§ z as to
NCI103dia GNIM
_ OJ
.2
O 3
& M
U
~ 3 2
LU 3 "3
1 t «
4J
5 s
_ Q
y si
~ 3
3J a.
3 3
? >
f8 flj
•< u
( U >D (333dS (3NIM
171
(quo 3dnSS3dd ~I3A3~! V3S
o
o
o
o
O
o
0)
co
I s -
en
05
cr>
3 C
U
NOIl03yiQ GNIM
(UM) a33dS GNIM
1 'J3 J
'- V 'J
3 -C l-i
•X - i
172
1
4
<D
S ^%^
1 *
O
u
■ 3
• <
o
c
>,
"
in
•
v-
•
4
T
03
s
•
jj
A
- 1
/
CJ
I
/
so
a.
4
(0
~ •
s |l
o
•
- *
<3
j .
-
•
•
31
c
*
h
<]
o
■;af
3
a
9
•3
r
s
■B — •
C
U5
2
<M
•
_
•
<3 <]
•
(0
<3
o
c
c
"•
*l
1*5
«
35
I •
3
03
_"
«
h *
a.
- 2 '
«3
J
a -L i
cvj
< a
>
<
< * ■-
3
-.- - 2
z
? < §
<3
<
u 5 -
S* 3
(0
O
2
< C £
< O 2
•
5
- 5 S <
<J»0
o
c
o i
c
o
3
o
r<j
Cjiuu) 33N71SIG "viava
173
A.3.5.3 Time Variation of R- Figure A. 18 shows the time variation of the radius
of maximum winds in Hurricane David from 0300 GMT September 2 to about 0800 GMT
September 5. Radial distances of maximum winds from the storm center measured by
reconnaissance aircraft at various times, and those obtained from analyses of
land-station wind records were used to obtain this time history.
Reconnaissance aircraft reported the majority of maximum winds needed for
R-value analyses, especially before 1200 GMT September 3. The line shown was
drawn to the data by eye.
As Figure A. 18 shows, the radius varied from about 17 to about 28 nmi
(31.5-51.9 km) between 2100 GMT September 2 and 1200 GMT September 3. By
1400 GMT September 3, land stations were beginning to experience maximum winds.
West Palm Beach, Florida experienced maximum winds when the hurricane center was
about 18 nmi from the station. Stuart, Florida recorded maximum winds at about
1600 GMT September 3 or 1.5 hours before the storm center made landfall in
Florida. The radius of maximum winds remained steady at 2 6 nmi (48.1 km) during
landfall. By 2100 GMT September 3, the radius began decreasing again until about
0100 GMT September 4 when a reconnaissance aircraft reported maximum winds at a
radius of 20 nmi (37 km). The radius remained steady once again at 20 nmi
(3 7 km) as the storm moved out over water north of Cape Canaveral (see
fig. A.ll). Both Melbourne and Shuttle Airport, Florida, experienced maximum
winds when David was located 20 nmi (37 km) from the station before exiting the
coast. From about 1030 GMT September 4 until landfall in Georgia at 1822 GMT,
the radius of maximum winds decreased to 10 nmi (18.5 km), as determined from
maximum winds recorded by a reconnaissance aircraft at about 2000 GMT. This was
the smallest radial distance reported within 150 nmi (2 78 km) of the east
coast. Hunter AFB and Savannah, Georgia, both recorded maximum winds soon after
the storm center made landfall when David was located 10 nmi (18.5 km) to the
south. After passing Savannah, Georgia, the radius of maximum winds expanded
rapidly. Columbia, South Carolina, experienced maximum winds when the storm was
located at a distance of about 47 nmi (87 km) from the station at 0600 GMT
September 5.
Because of the abrupt change in storm size after making landfall, using an
R value of 10 nmi (18.5 km) in a numerical surge computation could not replicate
surge heights along the coast produced by Hurricane David (Jarvinen 1985, private
communication). As David moved parallel to the coast and passed some 40 nmi
(74 km) inland of Charleston, South Carolina, its track and R influenced the
position of the band of strongest winds along the coast. This factor, in turn,
affected the coastal surges and the maximum wind setup effects in Charleston
Harbor. In replicating high water levels experienced in Charleston, either
varying R with time or using a large R value in a numerical surge computation
would be required in order to obtain realistic results.
A.4 Hurricane Allen, August 2-10, 1980
A. 4.1 Introduction
Hurricane Allen originated near the Cape Verde Islands, off the west coast of
Africa, and developed into the second most severe Atlantic hurricane in modern
records. It reached tropical storm strength in the early hours of
August 2, 1980, and attained hurricane strength that evening (see fig. A. 19).
Its central pressure dropped to 951 mb by the evening of the 3rd as the eye
passed just north of Barbados and south of St. Lucia. The hurricane continued
westward into the Caribbean at about 2 kn and passed south of Puerto Rico during
174
175
the evening of the 4th. Its central pressure deepened and reached 911 mb, the
lowest pressure ever recorded in the eastern Caribbean, on the early morning of
the 5th.
The hurricane weakened as it passed the southwest tip of Haiti and moved
between Jamaica and Cuba. This was the first of three strengthening-weakening
cycles in Allen's life history that are unprecedented in hurricane records.
Allen reintensified rapidly as the circulation moved over the northwestern
Caribbean Sea. Arriving at Yucatan Channel on the 7th, its central pressure
deepened to 899 mb, the lowest pressure ever observed in the western Caribbean
and the second lowest ever recorded for an Atlantic storm. The hurricane
weakened for the second time when it moved past the north coast of the Yucatan
peninsula. Its central pressure rose rapidly, reaching 961 mb on the morning of
the 8th. As the hurricane continued west-northwestward across the warm open
water of the Gulf of Mexico, Allen deepened once again with a minimum pressure of
909 mb observed during the night of the 8th.
As the hurricane approached the Texas coast on the 9th, its intensity weakened
and the forward speed decreased. Allen held to its west-northwesterly course
until mid-day and then turned northwestward. After crossing the southern end of
Padre Island just northeast of Brownsville, Texas, Allen continued in a
northwesterly direction. By early morning of the 10th, Allen moved inland at a
slightly faster speed and turned gradually towards the west-northwest. In
addition to the damage from the hurricane winds and storm surge, Hurricane Allen
also spawned at least a dozen tornadoes over Texas.
A.4.2 Previous Reports
The National Hurricane Center provided a description of significant features of
all Atlantic tropical storms that occurred during 1980, including Hurricane
Allen. This information was published in the Monthly Weather Review (Lawrence
and Pellissier 1981) and in the National Summary of Climatic Data (National
Hurricane Center 1980). Significant features mentioned in regard to Allen were
the minimum central pressure of record, the rapid deepening, and the fluctuations
in intensity during its life cycle. The appearance of a double eye configuration
was noted in a Brownsville radar picture taken when Allen was 100 nmi (185 km)
off the coast.
Willoughby et al. (1982) described secondary wind maxima associated with
concentric eye walls and the evolution of the hurricane vortex in Allen and a few
other hurricanes. They described the sequence of events as reported near Allen's
inner core by reconnaissance aircraft on August 5 and 8, 1980. Based on data
collected in Allen and other hurricanes, they concluded that an outer maximum is
frequently observed to constrict about a pre-existing eye and replace it and the
central pressure tends to decrease during the constriction. They suggest that
the concentric eye phenomenon is most frequently observed in intense, highly
symmetric systems.
The NHC publication on annual data and verification tabulation for the 1980
Atlantic tropical cyclones (Taylor and Staff 1981) also includes a list of
Allen's center fix positions obtained by aerial reconnaissance penetrations,
satellite images, and land-based radar. The hurricane's central pressure,
maximum winds, and other data observed by reconnaissance aircraft are also
included in that report.
176
Ho and Miller (1983) analyzed available meteorological data for Hurricane Allen
during the period surrounding landfall to provide information for use in dynamic
storm surge models. Detailed analyses were made of the storm track, forward
speed, central pressure, and radius of maximum winds.
Marks (1985) studied the evolution of the structure of precipitation in
Hurricane Allen. He used reflectivity data from airborne radar systems on board
the three NOAA aircraft to specify the horizontal and vertical precipitation
distributions within 111 km (60 nmi) of the hurricane center. He found that the
most striking changes in structure during the 6-day period were the rapid con-
traction in eyewall radius and the development of a secondary ring of intense
reflectivity 80-100 km (43-54 nmi) from the storm center. He further stated that
these changes in eye radius appeared to be related to the vortex evolution, as
discussed by Willoughby et al.
A.4.3 Reconnaissance Flight Data
NOAA/RFC research aircraft flew 12 missions into Allen during the 6 day period,
from August 5-10. Table A. 2 lists the flight patterns, flight levels and the
time periods for which meteorological and flight data were recorded in each of
the 12 missions. The table lists two 3-aircraft missions flown on August 5 and
August 8 and single-aircraft missions on other days. Willoughby et al. (1982)
compared the calculated and observed properties of Hurricane Allen on August 8
for all three different flight levels (500-, 600-, and 850-mb levels). He
concluded that one can obtain reliable indications of the evolution of the
symmetric vortex from any lower tropospheric flight level above the boundary
layer.
A.4.4 Central Pressure Analysis
Figure A.2 1 shows our analysis of the pressure information from reconnaissance
aircraft that was used to obtain a time history of Allen's central pressure.
This figure clearly shows the three strengthening-weakening cycles. Allen
reached a record low pressure (for specific areas) at each of its deepening
stages. A minimum pressure of 899 mb observed at 1742 GMT on August 7 was the
lowest observed in Hurricane Allen. The central pressure was only 7 mb higher
than the record pressure of 892mb observed in the Labor Day, 193 5 storm that
struck the Florida Keys. The low pressure of 909 mb, observed at 0558 GMT on
August 9, was considered to be the lowest that occurred in Hurricane Allen as it
approached the coast. The short time interval between central pressures obtained
by aircraft, combined with other information, did not indicate any lower pressure
at intermediate times. As Allen continued its course west-northwestward,
approaching the Texas coast, its intensity weakened. While the hurricane's
central pressure rose steadily, the characteristics of its inner core appeared to
have undergone dramatic changes, as discussed in the next section.
A.4.5 Wind Analysis
Flight-level winds on each traverse were plotted by computer and made available
to us by the Hurricane Research Division of NOAA/AOML. The aircraft locations
for observation of flight-level winds were translated to positions relative to
the storm center. From these records, composite maps of winds at given intervals
were constructed. Another source of information came from Air Force
reconnaissance aircraft that flew into the hurricane.
177
Table A.2. — Time, flight pattern, and flight level of NOAA/RFC missions into
Hurricane Allen, August 1980
Mission Time period
(GMT)
Pattern(s)
Flight level(s)
(ft)
800805F
800805H
8008051
800806H
80080 61
800807H
800808F
800808H
8008081
8008091
800809H
80081 OF
05/1028-1742
05/102 1-1933
05/1015-
06/1239-
06/1825-
07/1601-
08/162 0-
08/1631-
08/1617-
09/162 5-
09/2324-
10/1006-
■1932
-1910
•07/0031
•08/0017
•09/0059
■09/0107
•09/0110
•10/02 10
•10/0947
•1630
figs. A.2 0a, A.2 0b
fig. A.20a
fig. A.2 0b
fig. A.20a, A.20b
fig. A. 12
fig. A.20a (modified)
fig. A.2 0a (modified)
cross
along coast
2 5 nmi off coast
10,000
variable
variable
1,500, 5,000
1,500, 10,000 (last half)
5,000
variable
12 ,000
18,000, 20,000
5,000
10,000
variable
700- and 850-mb levels
'The missions are designated
YY = vear
MO = month
DA = dav of the month
by an identification code, YYMODAAC where:
F = NOAA/RFC C130B aircraft 41
<fH = NOAA/RFC WP-3D aircraft 42
I = NOAA/RFC WP-3D aircraft 43
Figure A.22 is an example of flight-level windspeeds plotted against radial
distances from the storm center. The wind data were recorded in a 3 12° to 132°
traverse through the eye between 153 5 and 1627 GMT on August 5. The maximum
winds can be located at radial distances of 15 and 19 nmi (27.8 and 35.2 km). A
secondary maximum appeared near radial distances of 50-60 nmi (82.6-111 km) at
the rear quadrant of the storm. At this time, Allen's central pressure had risen
to 93 7 mb, after having reached a minimum of 911 mb at 0000 GMT on the 5th
(fig. A.2 5). Figure A. 23 is another example of flight-level windspeed plotted
against radial distances from the storm center. This plot shows wind data
observed between 1844 and 1945 GMT on August 7. The maximum winds recorded
during this north to south traverse through the storm center were located at
radial distances of 5 and 10 nmi (9.3 and 18.5 km). The maximum winds decreased
rather rapidly with increasing distance away from the center. Allen, at this
time, was a small and extremely intense hurricane, having reached its minimum
pressure of 899 mb less than 2 hours earlier (see fig. A.2 1). Figure A.24 is an
178
(b)
DIRECTION OF STORM MOVEMENT
1
~50nmi
v^^ ~i5nmi
Figure A-20, — Reconnaissance flight patterns used in Hurricane Allen (refer Co
Friedman et al. 1982).
179
7/00 06
8/00 06 12 18 9/00 06 12 18 10/00 06 12
TIME (GMT)
Figure A-2 1. —Central pressure (sea level) for Hurricane Allen,
3-7, and (b) August 7-10, 1980.
(a) August
example of flight-level windspeed plotted at translated positions relative to Che
storm center. The wind data were observed between 02 00 and 0400 GMT on August 9
during the third deepening cycle within Allen's life span. The wind distribution
indicates that maximum winds occurred at radial distances of 11 nmi (20.4 km) and
about 54 ami (100 km) from Che center. Similar distributions of flight-level
winds can be identified in composiCe maps of other time periods (diagrams not
shown) as Allen approached Che Texas coast. The evolution of Che wind
distribution in Allen during this period, shifting from a small size hurricane Co
one with R of about 40 nmi (74 km), was described by Ho and Miller (1983).
180
50 10 -30
STORM DISTANCE (km)
Figure A-22. — Flight-level winds recorded along radials through the
Hurricane Allen, 1535-1627 GMT, August 5, 1980.
center of
9C
1 1 1 1 i 1 1 1
ft
30
i
A
-
^ 70
a
w so
a
/
\
-
UJ
U
a. 50
CO
a
| ,0
\
X
-
^^/W^
30
,
xx~^ -^X
20
i
-
10
1
i — i i i
-50 50
STORM DISTANCE Ckra)
Figure A .23. — Flight-level winds recorded along radials through the
Hurricane Allen, 1844-1945 GMT, August 7, 1980.
center of
181
30
30 60 90
DISTANCE (km)
Figure A.2 4. — Composite map of flight-level winds (m/sec) recorded between 0200
and 0400 GMT, August 9, 1980.
A.4.6 Time Variation of Central Pressure and Radius of Maximum Winds
Figure A.2 5 shows the time history of central pressure for Allen (from
fig. A.2 1) together with radial distances of observed maximum winds recorded at
each traverse of the hurricane center. Analysis of these radial distances
yielded the variation with time of the radius of maximum winds. Generally
speaking, Allen was a small hurricane except for the period when it approached
the Texas coast and moved over land. Prior to this period (9 hr before landfall)
the time variation of maximum winds indicated that the radial distances of wind
maxima increased to 2 0-2 5 nmi (3 7-46.3 km) during Allen's two weakening stages.
However, radial distances of wind maxima stayed within 4 to 15 nmi (7.4-2 7.8 km)
of the center when Allen's central pressure dropped below 93 mb in each of the
three deepening stages. The fact that Allen's minimum pressure in each of the
three deepening cycles occurred some distance from land, does not exclude the
possibility that a hurricane could attain its maximum intensity (or minimum
central pressure) at or near the time of landfall. Hurricane Camilla (1969) is
an example of a hurricane which maintained its intensity of about 90 5 mb for some
3 6 hours before it crossed the Mississippi coast.
A#4.7 Relation of ? and R in Hurricane Allen
Figure A.2 6 is a plot of central pressure versus radial distance of maximum
winds recorded by aircraft reconnaissance during the oeriod August 3 through
August 9. Data points used in the plot included those instances when both wind
182
o o o o o o
;*«•) 3anss3Hd
H
o
50
a
0^
w
v
<•
M
c
3
~"
!fl
aa
n
V
u
a
39
3
11
3
<
4J
c
B
—
I
<
in
0)
3
<
S3
■J
11
U
U
u
3
3
8C =
183
3 950
930
X A.F. RECON.
NOAA RECON.
/>
/
/
/
^ /
i
5 10 ^ 15 20
RAOIAL DISTANCE (nmi)
Figure A.2 6. — Concurrent observations of central pressure and radius of maximum
winds for Hurricane Allen, August 3-9, 1980.
and pressure data were recorded in a traverse of the hurricane center. Some of
the data points (with no concurrent observations of P and R) shown in previous
diagrams were not included in this plot. During the period of observation
(August 3-9), Allen traveled from the Caribbean through the Yucatan Channel into
the Gulf of Mexico. It covered a distance of about 2 ,000 nmi (3704 km) from
latitude 14°N through 27°N. Except for a few instances of larse R observed in
the weakening stages, Allen's maximum winds stayed within 15 nmi (27.8 km) of the
center. Allen was essentially characterized by small R's before it reached the
Texas coast. However, the R values in Allen, as well as in other intense
Atlantic hurricanes, tend to be small and a non-linear relation may exist between
P and R.
o
184
APPENDIX B
Statistical Methods for Tests of Homogeneity and Independence
B.l Introduction
The statistical methods used in this report to test the homogeneity of
hurricane parameters and interrelations between them are discussed in this
appendix. The methods used to test for homogeneity include cluster analysis,
discriminant analysis, principal component analysis, and the Mann-Whitney test;
those for the test of independence include the Spearman test and contingency
table analysis using the Chi-square test.
For these methods, this appendix describes assumptions, and where appropriate,
the null hypotheses, the confidence levels, and decision rules. We also briefly
discuss the rationale for choosing a method, its limitations, and the guidelines
for interpreting the test results.
B.2 Methods for the Test of Homogeneity
Among the methods for the test of homogeneity, cluster analysis, discriminant
analysis and principal component analysis each consider several parameters,
whereas the Mann-Whitney test is based on only a single parameter.
B«2.1 Cluster Analysis
B.2. 1.1 Description of the Method. In cluster analysis, objects are assigned to
groups or clusters suggested by the data sample, not by any grouping defined a
priori. In this study, a hurricane was considered an object for the purpose of
statistical analysis. That is, all parameters associated with a given storm were
used to characterize the hurricane. There are many clustering methods (e.g., SAS
1982); we chose the centroid method for this study.
The actual computation was performed using the CLUSTER procedure in the SAS
system. The procedure computes the Euclidean distances between objects and
assigns those objects that are close to each other to the same cluster. In this
study, the Euclidean distance was computed using coordinates represented by P ,
R, 9, T, m, (b and A. In the centroid method, the distance between two clusters
is defined as the Euclidean distance between their centroids (vector means).
The procedure provided a cluster hierarchy from level one to level N, where N
is the number of objects in the data sample. In this study, N is the number of
hurricanes; if any hurricane parameter was missing, that hurricane was omitted.
In the cluster hierarchy, there is only one cluster at level one and there are N
clusters at level N. The cluster at level one contains all the objects in the
data sample, and every cluster at level N contains only one object. As shown in
Figure B.l, every cluster at a given level is completely contained in a cluster
at the preceding level. For example, a cluster at level four may contain
Mention of a particular commercial product should not be considered an
endorsement by the federal government.
185
MILEPOST
NUMBER OF CLUSTERS
RANGE
2
3
4
5
6
7
8
9
11-243
©
©
©
©
©
©
©
296-500
o
©
560-671
©
©
©
©
©
©
718-904
966-1201
©
©
©
©
1292-1584
©
©
©
©
©
©
©
©
1752-1945
©
©
©
©
©
©
©
2043-2294
©
©
©
2532-2750
©
©
©
©
©
©
Figure B.l. — Levels two through nine of the hierarchical clusters of landf ailing
hurricanes, based on parameters P , R, 9, T, m, d> and \ . The circled numbers
are the cluster identification numbers.
exactly the same objects of one cluster at level five (cluster 2 in fig. B.l), or
it may' contain exactly the same objects of two clusters at level five (cluster 1
at level 4, and clusters 1 and 4 at level 5 in fig. B.l). The user must
determine the most appropriate number of clusters. When the number of clusters
is chosen, the parent cluster of each object (hurricane) can be identified using
the TREE procedure of the SAS system.
B.2.1.2 Rationale for Choice. Some clustering methods recuire that the sample
data be normally discributed. The hurricane data sample has large natural
variability, and' the normality of our data could not be reliably tested. We
chose to use the SAS CLUSTER Drocedure since it did not reauire that the data
sample be normal.
186
B.2.1.3 Limitations of the Method. No satisfactory method has heen developed to
determine the appropriate number of clusters. This is dependent on the data
sample and nature of the phenomena being considered.
B.2.1.4 Interpretation of the Results. Conclusions drawn from cluster analysis
are dependent on the selection of the number of clusters and must be interpreted
cautiously. Scatter diagrams of the original parameters were helpful for the
determination of the optimum number of clusters. Other methods, both
nonstatistical and statistical, were also considered to help interpret the
results of cluster analysis. In this study, we relied heavily on meteorological
judgment; in addition we used discriminant analysis and principal component
analysis to help evaluate the results of the cluster analysis.
B.2.2 Discriminant Analysis
B.2.2.1 Description of the Method. Discriminant analysis uses one
classification variable and several continuous quantitative variables to assign
each object to a class corresponding to a value of the classification variable
using the information contained in the continuous variables. In this study,
hurricanes were the objects to be classified, the cluster identification number
obtained from the cluster analysis was the classification variable, and
hurricane parameters were the continuous variables.
There are several types of discriminant analysis, some are based on the
assumption that each class can be considered normally distributed while others
use non-parametric methods and do not require the assumption of normality. In
this study, we used the "k-neares t-neighbor" discriminant analysis, where k was
chosen to be seven, equal to the number of parameters (P , R, 9, T, m, 4> and A)
used in the analysis.
Considering each hurricane as an object represented by a vector of seven
components (P R, 9, T, m, <t> and A), the method computes the distance between
two objects based on the total-sample covariance matrix (Mahalanobis distance),
and, for each object, it saves the distances of the seven nearest objects
(because k = 7). Based on these distances, it computes the probability that an
object would fall into the class with the selected nucleus object. If the
probability exceeds a specified threshold, the associated object is classified
into that class. The actual computation was performed using the NEIGHBOR
procedure of the SAS system. More details of the method are given in the SAS
User's Guide (SAS 1982).
B.2.2 .2 Rationale for Choice. The k-nearest-neighbor approach was non-
parametric and did not require the assumption of normality. It allowed us to
evaluate the results of the cluster analysis and to determine a number of
clusters that could be characterized as homogeneous for testing the independence
of the various hurricane parameters.
B.2.2 .3 Limitations of the Method. The variables, except for the classification
variable, must be continuous, so that the computation of distances can be
performed. The classification variable can be either categorical or numerical,
but there can only be one classification variable. It is recommended that the
classification variable be limited to a finite number of values, so that the
classes can be kept to a manageable number.
187
3.2.2.4 Interpretation of the Results. The discriminant analysis gives the
classification of each object and probabilities of its membership in all the
classes in which it could have been placed. By comparing the class that the
object was placed in and the class assigned a priori, misclassif ied objects can
be identified. The probability of membership in a particular class can be used
to judge whether the classification of the object was appropriate. The threshold
probability for the classification is user specified. In this study, the
threshold probability was not assigned and objects were classified into the
class which was associated with the largest membership probability.
3.2.3 Principal Component Analysis
3.2.3.1 Description of the Method. Given N numerical characteristics that
describe a set of objects, the principal component analysis procedure computes N
principal components; each principal component is a linear combination of the
original characteristics (variables). The coefficients of this linear
combination are the elements of an eigenvector of the correlation or covariance
matrix of the original variables. The eigenvectors are normalized to have unit
length (unit norm). The eigenvalues are the variances of the associated
principal components. The first principal component has the largest eigenvalue
and the N-th principal component has the smallest. The eigenvectors are
orthonormal, i.e., they represent perpendicular directions in the space of
original characteristic variables. In this study, the original characteristic
variables were P , R, 9, T, m, <j) and \ therefore, there were seven principal
components.
The computation of the principal components of the hurricane parameters was
performed using the PRINCOMP procedure of the SAS system. The procedure gives
the percentage and cumulative percentage of all eigenvalues ordered from the
largest to the smallest, i.e., from the first principal component to the seventh
principal component. These percentages show the relative amount of variance
accounted for by the principal components. The procedure also gives eigenvectors
whose elements are interpreted as the loadings on the original variables; the
loadings explain the relative importance of the hurricane parameters in each
principal component.
3.2.3.2 Rationale for Choice. After investigating the results of cluster
analysis and discriminant analysis, we decided to examine the importance of
various parameters in the grouping of hurricanes. The loadings provided with the
principal component analysis allowed us to evaluate the weight of individual
parameters. By plotting one principal component versus another and using the
cluster identification number of each hurricane for the plotting symbol, we could
examine the clustering patterns of the hurricanes. Using such a plot, we could
deduce which parameter(s) had most control on the clustering.
B.2.3.3 Limitations of the Method. Principal component analysis required that
all seven parameters P , R, 0, T, m, (f> and A be available for each hurricane.
Storms with missing values had to be excluded from the analysis.
B.2.3.4 Interpretation of the Results. As explained above, the results of the
principal component analysis can be used to explain the relative importance of
the original variables for the grouping of hurricanes. By investigating the
percentage of variance accounted for by each principal component, we were able to
188
select Che more important principal components. Then, by examining the
eigenvectors associated with these principal components, we found the original
variables that were most important in defining these principal components.
Although the results of the principal component analysis can be used to explain
some linear relations between the hurricane parameters, interpretation of these
relations was not always clear. Sometimes scatter diagrams of the original
variables were used for additional .guidance in understanding the results.
B.2.4 Mann-Whitney Test
B.2.4.1 Description of the Method. The Mann-Whitney test is a rank test
(non-parametric). In this study, we divided the hurricanes into several a priori
groupings based on location along the coast. For each test, we selected two
groups of hurricanes: one group had N hurricanes and the other had M
hurricanes. Assuming that each group was a random sample drawn from its
respective population and two groups were mutually independent, we performed the
Mann-Whi tney test on each of the hurricane parameters P , R and T.
The test was performed in the following manner: We first combined the group of
N hurricanes (group 1) with the group of M hurricanes (group 2). To test whether
parameter P , for example, has the same distribution function in groups 1 and 2 ,
we first arranged the P Q in the mixed sample from the smallest to the largest
value and assigned rank values from 1 to N+M to these P values. For tied values
of P , an averaged rank value was assigned to each of them as shown in the
following example (note rank 6.5 for P
961.7)
Example
Rank
Group Origin
943.0
947.2
955.3
956.7
959.0
961.7
961.7
966.5
975.0
979.0
981.0
1
2
2
2
3
2
4
1
5
2
6.5
2
6.5
1
8
1
9
1
10
2
11
1
Then, the sums of ranks (S) were computed separately for groups 1 and 2. In the
38.5 and S = 27.5,
The corresponding test statistics of the
Mann-Whitney test were computed using the formulae:
This example is for illustration only, not to be confused with any actual
grouping in this study.
189
W x = S 1 - \ N (N + 1), » 2 -S' 2 - 2 -M(M+l)
respectively for groups 1 and 2. In the example, N = 5 and M = 6,
and W2 = 6.5.
For given sample sizes N and M, percentiles of the Mann-Whitney test statistic
can be computed (see Conover, 1971, table 8). We used a two-tailed test at
5-percent significance level and the null hypothesis that P Q had the same
distribution function in both groups of hurricanes. For N = 5 and M = 6 in the
example, the 0.025-th percentile was 4 and the 0.975-th percentile was 26.
Comparing the test statistics Wj and W 2 with these percentiles, we found that W,
and W 2 were within the range between 4 and 2 6 (respectively, 0.025-th and
0.975-th percentiles), and we accepted the null hypothesis for the above example.
The test was repeated for R and T for every selected pair of groups of
hurricanes in this study. For more details of the Mann-Whitney test, see
Conover (1971).
3.2.4.2 Rationale for Choice. The limited sample size and large natural
variability of our hurricane data sample prevented us from reliably estimating
the distribution functions of hurricane parameters for formal hypothesis
testing. Since the Mann-Whitney test is a non-parametric test, it does not
require a priori assumptions about the distribution function of the data sample
and is suitable for our hurricane data.
B.2.4.3 Limitations of the Method. The basic assumption for the Mann-Whitney
test is that both groups are drawn as random samples. For the reasons discussed
in Section 3.2.1.2, we did not consider it appropriate to use direction of
landf ailing hurricanes as a random variable, and this parameter was excluded
from the Mann-Whitney test. Another assumption of the Mann-Whitney test is that
two samples must be mutually independent. There was no evidence that our
hurricane data samples for the selected coastal segments violated this
assumption.
B.2.4.4 Interpretation of the Results. The Mann-Whitney test examines the
similarity of two distributions of rankings, but not the distributions of the
actual values of the hurricane parameters. For this reason, the results must be
interpreted with caution, and any conclusions drawn from the test results must
recognize that the distributions of rankings may not fully correspond to the
distributions of the actual values.
B.3 Methods for the Test of Independence
To test independence among hurricane parameters, we used two methods: the
Spearman test and contingency tables with the Chi-square test. The Spearman test
is a rank test while the contingency tables with the Chi-square test is for
categorical data.
190
B.3.1 Spearman Test
B.3.1.1 Description of the Method. As an example, consider the Spearman test
for P and R for a group of hurricanes. P Q was ranked from the smallest to the
largest value and rank numbers were assigned to each value; for tied values of
P , an average rank value was assigned to each of them as was done in the
Mann-Whitney test (see sec. B.2.4.1). For the same group of hurricanes, R's were
also ranked and assigned a rank number. Then the Spearman correlation was
computed using the following formula:
P = 1 -
6W
N 2
N (IT-1)
where W = V" [r(P Q ) - r(R.)] 2
The parameter N is the sample size of the group of hurricanes, and r is the rank
value of parameters P Q or R. Spearman's correlation can be used as a test
statistic. Given the sample size, N, and the probability of a percentile, this
percentile can be computed.
There are three ways to test the Spearman correlation. The null hypothesis for
all three tests is that P and R are mutually independent, that is, the
correlation coefficient is not significantly different from zero. The alternate
hypothesis for the first test is that P and R are positively correlated, for the
second, that P and R are negatively correlated, and for the third, that P and R
are correlated (either positively or negatively). In this study, when the
probability associated with a specific estimate of P was greater than
95th percentile, we rejected the null hypothesis of the first test, when p was
less than 5th percentile, we rejected the null hypothesis of the second test, and
when p was either less than 2.5 percent or greater than 97.5 percent, we rejected
the null hypothesis of the third test. The significance level for all the tests
was 5 percent. For more details, see Conover (1971).
B.3.1. 2 Rationale for Choice. We chose Spearman test for the hurricane
parameters because it offered the possibility of detecting the nature of
interrelations, if they existed.
B.3.1. 3 Limitations of the Method. As with many non-parametric tests, weak
relations between two parameters may not be detected.
B.3.1. 4 Interpretation of the Results. The Spearman test detects the
correlation of ranks of random variables instead of the actual values of the
variables. The interpretation of these correlations should be limited to the
correlations of ranks only; independence between ranks of random variables may
imply independence of the random variables.
191
B.3.2 Contingency Table with Chi-square Test
B.3.2.1 Description of the Method. The contingency table with a Chi-square test
was used at the 0.05 level and is described in detail in Section 4.2 of this
report. Additional details may be found in Conover (1971).
B.3.2 .2 Rationale for Choice. There was no requirement that the sample meet
conditions other than it be a random sample of sufficient size. This made it
suitable for use with our data sample.
B.3.2 .3 Limitations of the Method. The contingency table with the Chi-square
test was designed for categorical data samples, thus, we had to choose specific
values to partition the parameters into categories to establish the cell
frequencies in the contingency table. There cannot be more than 2 percent of
cells which have expected frequency less than 5 in each of them. This limitation
is to ensure that the Chi-square approximation is valid for the test.
B.3.2 .4 Interpretation of the Results. The results of this test were sensitive
to the values selected to partition the data into categories. A small change of
the dividing value sometimes caused the result to change from not significant to
significant, or vice versa. Therefore, we had to be careful in interpreting the
results using this approach.
APPENDIX C
Plotting Position Formula
C.l Introduction
A plotting position formula was used to determine the location along the
abscissa of ranked data in the cumulative frequency curves for the hurricane
parameters. A plotting position formula was selected for this purpose from eight
existing formulae based upon five evaluation criteria.
Existing plotting position formulae are listed in Table C.l. The symbols used
in the formulae are explained in the note underneath the table. In each line,
the name of the formula is given in the left column, and the year in which the
formula was introduced is given in the right column. This table does not include
all existing formulae. The Beard (1943) formula is not included because it only
applies to m = 1, and the Samsioe formula (see Reinius 1949, p. 51) is not
included because its computation involves solving a N-th power equation and it is
not easy to use. For convenience of computation, only easy-to-use formulae were
considered.
C.2 Criteria for Evaluation
The plotting position formula listed in Table C.l were evaluated according to
the criteria listed below.
1. The plotting position must be such that all the observed data can
be plotted on probability paper.
192
Table C.l. — List of plotting position formulae
Name Formula ' Year
California P„, = -£- 1923
m N
Hazen P„, = 2 ?~ 1 193
m ZN
Wei bull P m = t~ 193 9
m N+l
Chegodayev P„ = g~j 1955
Blora P = *.',, 1958
m
N+0.4
m-3/8
m
N+l/4
3m-l
m
3N+1
m-0.44
m
N+0.12
> —
m-0.3 7
Tukey P = ";" t 1962
J m 3N+1
m -0 .44
Gringorten P m = „, n ,_ 1963
Reinius P = !" " '" 4 1982
m N+0 .2 6
P = probability;
Til
N = total number of items;
m = rank of an item
m < N.
2. Tbe plotting position sbould lie between the observed frequencies
(m-l)/N and m/N. (For the explanation of m and N, see the footnote
of Table C.l.)
3. The return period of a value equal to, or larger than, the largest
observed value should converge towards N.
4. The observed values should be equally spaced on the frequency
scale.
5. The plotting position should have an intuitive meaning, be
analytically simple, and be easy to use.
193
Table C.2. — List of plotting position formulae in the descending order of their
p * s. (See table C-l for the meanings of symbols.)
m = 1 m = N
California California
Wei bull Haze n
Chegodayev Gringorten
Tukey Blora
Reinius Reinius
Bl om Tukey
Gringorten Chegodayev
Hazen Wei bull
C.3 Evaluation of Plotting Position Formulae
All formulae in Table C.l meet criteria 4 and 5. All except tbe California
formula meet criteria 1 and 2. Only the California and Weibull formulae meet
criterion 3. The most important problem with the California formula is that it
gives p ffl = 100 percent for m = N, and this p can not be plotted on a probability
paper. The most important advantage of Weibull formula is that tbe return period
for m = 1 converges towards N as N * oo. Among formulae listed in Table C.l,
only the Weibull formula meets all tbe criteria listed above. Thus, the Weibull
formula was the choice used in this study.
C.4 Comparison of Formulae
To reveal more about the characteristics of the various formulae, we compared
them for the special cases: m = 1, m = N, and N » oo. For m = 1 and N, the
names of formulae are listed in Table C.2 in the descending order of their values
of p . The order of names for m = N is exactly the reverse of that for m = 1,
except for California formula. For N » oo, the values of p computed using all
the formulae in Table C.l approach m/N.
Since the sample size of hurricane clima tological data is usually small, we
choose N = 10 for an example to compare values of p of the formulae in
Table C.l. These values are plotted in Figure C.l. The Weibull formula gave the
largest p for m = 1 and the smallest p for m = N. Except for the California
formula, the largest difference in p between different formulae was less than
5 percent. For m = 1, the p of the Weibull formula is approximately two times
that of the Hazen formula. For m = N, the p of the Weibull formula is close to
' r m
that of the Hazen formula: approximately 91 percent compared to 95 percent.
194
3
7
6
m s
4
3
2
CALIFORNIA
HAZEN
WEIBULL
CHEGODAYEV
1 0.1 0.2 0.5 I 2 5 10
m
90 95 99 99.6 99. 9<
Figure C.l .--Comparison of plotting position formulae for N = 10. (See Cable C.l
for the meanings of symbols.)
95
(Continued from inside front cover)
NWS 16 Storm Tide Frequencies on the South Carolina Coast. Vance A. Myers, June 1975, 79 p. (C0M-75-
11335)
NWS 17 Estimation of Hurricane Storm Surge in Apalachicola Bay, Florida. James E. Overland, June 1975.
66 p. (COM-75-11332)
NWS 18 Joint Probability Method of Tide Frequency Analysis Applied to Apalachicola Bay and St. George
Sound, Florida. Francis P. Ho and Vance A. Myers, November 1975, 43 p. (PB-251123)
NWS 19 A Point Energy and Mass Balance Model of a Snow Cover. Eric A. Anderson, February 1976, 150 p.
(PB-254653)
NWS 20 Precipitable Water Over the United States, Volume 1: Monthly Means. George A. Lott, November
1976, 173 p. (PB-264219)
NWS 20 Precipitable Water Over the United States, Volume II: Semimonthly Maxima. Francis P. Ho and
John T. Riedel, July 1979, 359 p. (PB-300870)
NWS 21 Interduration Precipitation Relations for Storms - Southeast States. Ralph H. Frederick, March
1979, 66 p. (PB-297192)
NWS 22 The Nested Grid Model. Norman A. Phillips, April 1979, 89 p. (PB-299046)
NWS 23 Meteorological Criteria for Standard Project Hurricane and Probable Maximum Hurricane and
Probable Maximum Hurricane Windf ields , Gulf and East Coasts of the United States. Richard W.
Schwerdt, Francis P. Ho, and Roger R. Watkins , September 1979, 348 p. (PB-80 117997)
NWS 24 A Methodology for Point-to-Area Rainfall Frequency Ratios. Vance A. Myers and Raymond M. Zehr,
February 1980, 180 p. (PB80 180102)
NWS 25 Comparison of Generalized Estimates of Probable Maximum Precipitation With Greatest Observed
Rainfalls. John T. Riedel and Louis C. Schreiner, March 1980, 75 p. (PB80 191463)
NWS 26 Frequency and Motion of Atlantic Tropical Cyclones. Charles J. Neumann and Michael J. Pryslak,
March 1981, 64 p. (PB81 247256)
NWS 27 Interduration Precipitation Relations for Storms — Western United States. Ralph H. Frederick,
John F. Miller, Francis P. Richards, and Richard W. Schwerdt, September 1981, 158 p. (PB82 230517)
NWS 28 GEM: A Statistical Weather Forecasting Procedure. Robert G. Miller, November 1981, 103 p.
NWS 29 Analyses of Elements of the Marine Environment for the Atlantic Remote Sensing Land Ocean
Experiment (ARSLOE) — An Atlas for October 22 Through October 27, 1980. Lawrence D. Burroughs,
May 1982, 116 p. (PB82 251281)
NWS 30 The NMC Spectral Model. Joseph G. Sela, May 1982, 38 p. (PB83 115113)
NWS 31 A Monthly Averaged Climatology of Sea Surface Temperature. Richard W. Reynolds, June 1982, 37 p.
(PB83 115469)
NWS 32 Pertinent Meteorological and Hurricane Tide Data for Hurricane Carla. Francis P. Ho and John F.
Miller, August 1982, 111 p. (PB83 118240)
NWS 33 Evaporation Atlas for the Contiguous 48 United States. Richard K. Farnsworth, Edwin S. Thompson,
and Eugene L. Peck, June 1982, 26 p.
NWS 34 Mean Monthly, Seasonal, and Annual Pan Evaporation for the United States. Richard K. Farnsworth
and Edwin S. Thompson, December 1982, 85 p. (PB83 161729)
NWS 35 Pertinent Meteorological Data for Hurricane Allen of 1980. Frances P. Ho and John F. Miller
September 1983, 73 p. (PB 272 112)
NWS 36 Water Available for Runoff for 1 to 15 Days Duration and Return Periods of 2 to 100 Years for
Selected Agricultural Regions in the Northwest United States. Frank P. Richards, John F. Miller,
Edward A. Zurndorfer, and Norma S. Foat, April 1983, 59 p. (PB84 120591)
NWS 37 The National Weather Service Hurricane Probability Program. Robert C. Sheets, April 1984, 70 p.
(PB84 182757)
UNIVERSITY OF ILUNOIS-URBANA
3 0112102358121
NOAA SCIENTIFIC AND TECHNICAL PUBLICATIONS
The National Oceanic and Atmospheric Administration was established as part of the Department of
Commerce on October 3, 1970. The mission responsibilities of NOAA are to assess the socioeconomic impact
of natural and technological changes in the environment and to monitor and predict the state of the solid
Earth, the oceans and their living resources, the atmosphere, and the space environment of the Earth.
The major components of NOAA regularly produce various types of scientific and technical informa-
tion in the following kinds of publications:
PROFESSIONAL PAPERS— Important defini-
tive research results, major techniques, and special
investigations.
CONTRACT AND GRANT REPORTS— Reports
prepared by contractors or grantees under NOAA
sponsorship.
ATLAS — Presentation of analyzed data generally
in the form of maps showing distribution of rain-
fall, chemical and physical conditions of oceans and
atmosphere, distribution of fishes and marine
mammals, ionospheric conditions, etc.
TECHNICAL SERVICE PUBLICATIONS— Re-
ports containing data, observations, instructions,
etc. A partial listing includes data serials; predic-
tion and outlook periodicals; technical manuals,
training papers, planning reports, and information
serials; and miscellaneous technical publications.
TECHNICAL REPORTS— Journal quality with
extensive details, mathematical developments, or
data listings.
TECHNICAL MEMORANDUMS— Reports of
preliminary, partial, or negative research or tech-
nology results, interim instructions, and the like.
TVNews
OpenLibrary